idx int64 1 56k | question stringlengths 15 155 | answer stringlengths 2 29.2k ⌀ | question_cut stringlengths 15 100 | answer_cut stringlengths 2 200 ⌀ | conversation stringlengths 47 29.3k | conversation_cut stringlengths 47 301 |
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1,901 | What's the difference between correlation and simple linear regression? | All of the given answers so far provide important insights but it should not be forgotten that you can transform the parameters of one into the other:
Regression: $y = mx + b$
Connection between regression parameters and correlation, covariance, variance, standard deviation and means:
$$m = \frac{Cov(y, x)}{Var(x)} = \... | What's the difference between correlation and simple linear regression? | All of the given answers so far provide important insights but it should not be forgotten that you can transform the parameters of one into the other:
Regression: $y = mx + b$
Connection between regre | What's the difference between correlation and simple linear regression?
All of the given answers so far provide important insights but it should not be forgotten that you can transform the parameters of one into the other:
Regression: $y = mx + b$
Connection between regression parameters and correlation, covariance, va... | What's the difference between correlation and simple linear regression?
All of the given answers so far provide important insights but it should not be forgotten that you can transform the parameters of one into the other:
Regression: $y = mx + b$
Connection between regre |
1,902 | What's the difference between correlation and simple linear regression? | Correlation analysis only quantifies the relation between two variables ignoring which is dependent variable and which is independent. But before appliyng regression you have to calrify that impact of which variable you want to check on the other variable. | What's the difference between correlation and simple linear regression? | Correlation analysis only quantifies the relation between two variables ignoring which is dependent variable and which is independent. But before appliyng regression you have to calrify that impact of | What's the difference between correlation and simple linear regression?
Correlation analysis only quantifies the relation between two variables ignoring which is dependent variable and which is independent. But before appliyng regression you have to calrify that impact of which variable you want to check on the other v... | What's the difference between correlation and simple linear regression?
Correlation analysis only quantifies the relation between two variables ignoring which is dependent variable and which is independent. But before appliyng regression you have to calrify that impact of |
1,903 | What's the difference between correlation and simple linear regression? | From correlation we can only get an index describing the linear relationship between two variables; in regression we can predict the relationship between more than two variables and can use it to identify which variables x can predict the outcome variable y. | What's the difference between correlation and simple linear regression? | From correlation we can only get an index describing the linear relationship between two variables; in regression we can predict the relationship between more than two variables and can use it to iden | What's the difference between correlation and simple linear regression?
From correlation we can only get an index describing the linear relationship between two variables; in regression we can predict the relationship between more than two variables and can use it to identify which variables x can predict the outcome v... | What's the difference between correlation and simple linear regression?
From correlation we can only get an index describing the linear relationship between two variables; in regression we can predict the relationship between more than two variables and can use it to iden |
1,904 | What's the difference between correlation and simple linear regression? | Quoting Altman DG, "Practical statistics for medical research" Chapman & Hall, 1991, page 321:
"Correlation reduces a set of data to a single number that bears no direct relation to the actual data. Regression is a much more useful method, with results which are clearly related to the measurement obtained. The strength... | What's the difference between correlation and simple linear regression? | Quoting Altman DG, "Practical statistics for medical research" Chapman & Hall, 1991, page 321:
"Correlation reduces a set of data to a single number that bears no direct relation to the actual data. R | What's the difference between correlation and simple linear regression?
Quoting Altman DG, "Practical statistics for medical research" Chapman & Hall, 1991, page 321:
"Correlation reduces a set of data to a single number that bears no direct relation to the actual data. Regression is a much more useful method, with res... | What's the difference between correlation and simple linear regression?
Quoting Altman DG, "Practical statistics for medical research" Chapman & Hall, 1991, page 321:
"Correlation reduces a set of data to a single number that bears no direct relation to the actual data. R |
1,905 | What's the difference between correlation and simple linear regression? | The regression analysis is a technique to study the cause of effect of a relation between two variables.
whereas, The correlation analysis is a technique to study the quantifies the relation between two variables. | What's the difference between correlation and simple linear regression? | The regression analysis is a technique to study the cause of effect of a relation between two variables.
whereas, The correlation analysis is a technique to study the quantifies the relation between t | What's the difference between correlation and simple linear regression?
The regression analysis is a technique to study the cause of effect of a relation between two variables.
whereas, The correlation analysis is a technique to study the quantifies the relation between two variables. | What's the difference between correlation and simple linear regression?
The regression analysis is a technique to study the cause of effect of a relation between two variables.
whereas, The correlation analysis is a technique to study the quantifies the relation between t |
1,906 | What's the difference between correlation and simple linear regression? | Correlation is an index (just one number) of the strength of a relationship. Regression is an analysis (estimation of parameters of a model and statistical test of their significance) of the adequacy of a particular functional relationship. The size of the correlation is related to how accurate the predictions of the r... | What's the difference between correlation and simple linear regression? | Correlation is an index (just one number) of the strength of a relationship. Regression is an analysis (estimation of parameters of a model and statistical test of their significance) of the adequacy | What's the difference between correlation and simple linear regression?
Correlation is an index (just one number) of the strength of a relationship. Regression is an analysis (estimation of parameters of a model and statistical test of their significance) of the adequacy of a particular functional relationship. The siz... | What's the difference between correlation and simple linear regression?
Correlation is an index (just one number) of the strength of a relationship. Regression is an analysis (estimation of parameters of a model and statistical test of their significance) of the adequacy |
1,907 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | This is certainly a valid concern, but this isn't quite right.
If 1,000,000 studies are done and all the null hypotheses are true then approximately 50,000 will have significant results at p < 0.05. That's what a p value means. However, the null is essentially never strictly true. But even if we loosen it to "almost... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | This is certainly a valid concern, but this isn't quite right.
If 1,000,000 studies are done and all the null hypotheses are true then approximately 50,000 will have significant results at p < 0.05. | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
This is certainly a valid concern, but this isn't quite right.
If 1,000,000 studies are done and all the null hypotheses are true then approximately 50,000 will have significant results at p < 0.05. That's what a p v... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
This is certainly a valid concern, but this isn't quite right.
If 1,000,000 studies are done and all the null hypotheses are true then approximately 50,000 will have significant results at p < 0.05. |
1,908 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | Aren't all researches around the world somewhat like the "infinite
monkey theorem" monkeys?
Remember, scientists are critically NOT like infinite monkeys, because their research behavior--particularly experimentation--is anything but random. Experiments are (at least supposed to be) incredibly carefully controlled ... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | Aren't all researches around the world somewhat like the "infinite
monkey theorem" monkeys?
Remember, scientists are critically NOT like infinite monkeys, because their research behavior--particul | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
Aren't all researches around the world somewhat like the "infinite
monkey theorem" monkeys?
Remember, scientists are critically NOT like infinite monkeys, because their research behavior--particularly experimentati... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
Aren't all researches around the world somewhat like the "infinite
monkey theorem" monkeys?
Remember, scientists are critically NOT like infinite monkeys, because their research behavior--particul |
1,909 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | Your understanding of $p$-values seems to be correct.
Similar concerns are voiced quite often. What makes sense to compute in your example, is not only the number of studies out of 23 mln that arrive to false positives, but also the proportion of studies that obtained significant effect that were false. This is called ... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | Your understanding of $p$-values seems to be correct.
Similar concerns are voiced quite often. What makes sense to compute in your example, is not only the number of studies out of 23 mln that arrive | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
Your understanding of $p$-values seems to be correct.
Similar concerns are voiced quite often. What makes sense to compute in your example, is not only the number of studies out of 23 mln that arrive to false positives... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
Your understanding of $p$-values seems to be correct.
Similar concerns are voiced quite often. What makes sense to compute in your example, is not only the number of studies out of 23 mln that arrive |
1,910 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | Your concern is exactly the concern that underlies a great deal of the current discussion in science about reproducability. However, the true state of affairs is a bit more complicated than you suggest.
First, let's establish some terminology. Null hypothesis significance testing can be understood as a signal detecti... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | Your concern is exactly the concern that underlies a great deal of the current discussion in science about reproducability. However, the true state of affairs is a bit more complicated than you sugge | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
Your concern is exactly the concern that underlies a great deal of the current discussion in science about reproducability. However, the true state of affairs is a bit more complicated than you suggest.
First, let's e... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
Your concern is exactly the concern that underlies a great deal of the current discussion in science about reproducability. However, the true state of affairs is a bit more complicated than you sugge |
1,911 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | A substantial check on the important issue raised in this question is that "scientific truth" is not based on individual, isolated publications. If a result is sufficiently interesting it will prompt other scientists to pursue the implications of the result. That work will tend to confirm or refute the original finding... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | A substantial check on the important issue raised in this question is that "scientific truth" is not based on individual, isolated publications. If a result is sufficiently interesting it will prompt | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
A substantial check on the important issue raised in this question is that "scientific truth" is not based on individual, isolated publications. If a result is sufficiently interesting it will prompt other scientists t... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
A substantial check on the important issue raised in this question is that "scientific truth" is not based on individual, isolated publications. If a result is sufficiently interesting it will prompt |
1,912 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | Just to add to the discussion, here is an interesting post and subsequent discussion about how people are commonly misunderstanding p-value.
What should be retained in any case is that a p-value is just a measure of the strength of evidence in rejecting a given hypothesis. A p-value is definitely not a hard threshold b... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | Just to add to the discussion, here is an interesting post and subsequent discussion about how people are commonly misunderstanding p-value.
What should be retained in any case is that a p-value is ju | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
Just to add to the discussion, here is an interesting post and subsequent discussion about how people are commonly misunderstanding p-value.
What should be retained in any case is that a p-value is just a measure of th... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
Just to add to the discussion, here is an interesting post and subsequent discussion about how people are commonly misunderstanding p-value.
What should be retained in any case is that a p-value is ju |
1,913 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | As also pointed out in the other answers, this will only cause problems if you are going to selectively consider the positive results where the null hypothesis is ruled out. This is why scientists write review articles where they consider previously published research results and try to develop a better understanding o... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | As also pointed out in the other answers, this will only cause problems if you are going to selectively consider the positive results where the null hypothesis is ruled out. This is why scientists wri | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
As also pointed out in the other answers, this will only cause problems if you are going to selectively consider the positive results where the null hypothesis is ruled out. This is why scientists write review articles... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
As also pointed out in the other answers, this will only cause problems if you are going to selectively consider the positive results where the null hypothesis is ruled out. This is why scientists wri |
1,914 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | This is close to a very important fact about the scientific method: it emphasizes falsifiability. The philosophy of science which is most popular today has Karl Popper's concept of falsifiability as a corner stone.
The basic scientific process is thus:
Anyone can claim any theory they want, at any time. Science will... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | This is close to a very important fact about the scientific method: it emphasizes falsifiability. The philosophy of science which is most popular today has Karl Popper's concept of falsifiability as | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
This is close to a very important fact about the scientific method: it emphasizes falsifiability. The philosophy of science which is most popular today has Karl Popper's concept of falsifiability as a corner stone.
Th... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
This is close to a very important fact about the scientific method: it emphasizes falsifiability. The philosophy of science which is most popular today has Karl Popper's concept of falsifiability as |
1,915 | Is this really how p-values work? Can a million research papers per year be based on pure randomness? | Is this how "science" is supposed to work?
That's how a lot of social sciences work. No so much with physical sciences. Think of this: you typed your question on a computer. People were able to build these complicated beasts called computers using the knowledge of physics, chemistry and other fields of physical scienc... | Is this really how p-values work? Can a million research papers per year be based on pure randomness | Is this how "science" is supposed to work?
That's how a lot of social sciences work. No so much with physical sciences. Think of this: you typed your question on a computer. People were able to build | Is this really how p-values work? Can a million research papers per year be based on pure randomness?
Is this how "science" is supposed to work?
That's how a lot of social sciences work. No so much with physical sciences. Think of this: you typed your question on a computer. People were able to build these complicated... | Is this really how p-values work? Can a million research papers per year be based on pure randomness
Is this how "science" is supposed to work?
That's how a lot of social sciences work. No so much with physical sciences. Think of this: you typed your question on a computer. People were able to build |
1,916 | What is the best way to identify outliers in multivariate data? | Have a look at the mvoutlier package which relies on ordered robust mahalanobis distances, as suggested by @drknexus. | What is the best way to identify outliers in multivariate data? | Have a look at the mvoutlier package which relies on ordered robust mahalanobis distances, as suggested by @drknexus. | What is the best way to identify outliers in multivariate data?
Have a look at the mvoutlier package which relies on ordered robust mahalanobis distances, as suggested by @drknexus. | What is the best way to identify outliers in multivariate data?
Have a look at the mvoutlier package which relies on ordered robust mahalanobis distances, as suggested by @drknexus. |
1,917 | What is the best way to identify outliers in multivariate data? | I think Robin Girard's answer would work pretty well for 3 and possibly 4 dimensions, but the curse of dimensionality would prevent it working beyond that. However, his suggestion led me to a related approach which is to apply the cross-validated kernel density estimate to the first three principal component scores. Th... | What is the best way to identify outliers in multivariate data? | I think Robin Girard's answer would work pretty well for 3 and possibly 4 dimensions, but the curse of dimensionality would prevent it working beyond that. However, his suggestion led me to a related | What is the best way to identify outliers in multivariate data?
I think Robin Girard's answer would work pretty well for 3 and possibly 4 dimensions, but the curse of dimensionality would prevent it working beyond that. However, his suggestion led me to a related approach which is to apply the cross-validated kernel de... | What is the best way to identify outliers in multivariate data?
I think Robin Girard's answer would work pretty well for 3 and possibly 4 dimensions, but the curse of dimensionality would prevent it working beyond that. However, his suggestion led me to a related |
1,918 | What is the best way to identify outliers in multivariate data? | You can find a pedagogical summary of the various methods available in (1)
For some --recent-- numerical comparisons of the various methods listed there, you can check
(2) and (3).
there are many older (and less exhaustive) numerical comparisons, typically found in books. You will find one on pages 142-143 of (4), for... | What is the best way to identify outliers in multivariate data? | You can find a pedagogical summary of the various methods available in (1)
For some --recent-- numerical comparisons of the various methods listed there, you can check
(2) and (3).
there are many old | What is the best way to identify outliers in multivariate data?
You can find a pedagogical summary of the various methods available in (1)
For some --recent-- numerical comparisons of the various methods listed there, you can check
(2) and (3).
there are many older (and less exhaustive) numerical comparisons, typicall... | What is the best way to identify outliers in multivariate data?
You can find a pedagogical summary of the various methods available in (1)
For some --recent-- numerical comparisons of the various methods listed there, you can check
(2) and (3).
there are many old |
1,919 | What is the best way to identify outliers in multivariate data? | I didn't see anybody mention influence functions. I first saw this idea in Gnanadesikan's multivariate book.
In one dimension an outlier is either an extremely large or an extremely small value. In multivariate analysis it is an observation removed from the bulk of the data. But what metric should we use to define e... | What is the best way to identify outliers in multivariate data? | I didn't see anybody mention influence functions. I first saw this idea in Gnanadesikan's multivariate book.
In one dimension an outlier is either an extremely large or an extremely small value. In | What is the best way to identify outliers in multivariate data?
I didn't see anybody mention influence functions. I first saw this idea in Gnanadesikan's multivariate book.
In one dimension an outlier is either an extremely large or an extremely small value. In multivariate analysis it is an observation removed from ... | What is the best way to identify outliers in multivariate data?
I didn't see anybody mention influence functions. I first saw this idea in Gnanadesikan's multivariate book.
In one dimension an outlier is either an extremely large or an extremely small value. In |
1,920 | What is the best way to identify outliers in multivariate data? | I would do some sort of "leave one out testing algorithm" (n is the number of data):
for i=1 to n
compute a density estimation of the data set obtained by throwing $X_i$ away. (This density estimate should be done with some assumption if the dimension is high, for example, a gaussian assumption for which the density e... | What is the best way to identify outliers in multivariate data? | I would do some sort of "leave one out testing algorithm" (n is the number of data):
for i=1 to n
compute a density estimation of the data set obtained by throwing $X_i$ away. (This density estimate | What is the best way to identify outliers in multivariate data?
I would do some sort of "leave one out testing algorithm" (n is the number of data):
for i=1 to n
compute a density estimation of the data set obtained by throwing $X_i$ away. (This density estimate should be done with some assumption if the dimension is ... | What is the best way to identify outliers in multivariate data?
I would do some sort of "leave one out testing algorithm" (n is the number of data):
for i=1 to n
compute a density estimation of the data set obtained by throwing $X_i$ away. (This density estimate |
1,921 | What is the best way to identify outliers in multivariate data? | You can find candidates for "outliers" among the support points of the minimum volume bounding ellipsoid. (Efficient algorithms to find these points in fairly high dimensions, both exactly and approximately, were invented in a spate of papers in the 1970's because this problem is intimately connected with a question i... | What is the best way to identify outliers in multivariate data? | You can find candidates for "outliers" among the support points of the minimum volume bounding ellipsoid. (Efficient algorithms to find these points in fairly high dimensions, both exactly and approx | What is the best way to identify outliers in multivariate data?
You can find candidates for "outliers" among the support points of the minimum volume bounding ellipsoid. (Efficient algorithms to find these points in fairly high dimensions, both exactly and approximately, were invented in a spate of papers in the 1970'... | What is the best way to identify outliers in multivariate data?
You can find candidates for "outliers" among the support points of the minimum volume bounding ellipsoid. (Efficient algorithms to find these points in fairly high dimensions, both exactly and approx |
1,922 | What is the best way to identify outliers in multivariate data? | I novel approach I saw was by IT Jolliffe Principal Components Analysis. You run a PCA on your data (Note: PCA can be quite a useful data exploration tool in its own right), but instead of looking at the first few Principal Components (PCs), you plot the last few PCs. These PCs are the linear relationships between yo... | What is the best way to identify outliers in multivariate data? | I novel approach I saw was by IT Jolliffe Principal Components Analysis. You run a PCA on your data (Note: PCA can be quite a useful data exploration tool in its own right), but instead of looking at | What is the best way to identify outliers in multivariate data?
I novel approach I saw was by IT Jolliffe Principal Components Analysis. You run a PCA on your data (Note: PCA can be quite a useful data exploration tool in its own right), but instead of looking at the first few Principal Components (PCs), you plot the ... | What is the best way to identify outliers in multivariate data?
I novel approach I saw was by IT Jolliffe Principal Components Analysis. You run a PCA on your data (Note: PCA can be quite a useful data exploration tool in its own right), but instead of looking at |
1,923 | What is the best way to identify outliers in multivariate data? | It may be an overshoot, but you may train an unsupervised Random Forest on the data and use the object proximity measure to detect outliers. More details here. | What is the best way to identify outliers in multivariate data? | It may be an overshoot, but you may train an unsupervised Random Forest on the data and use the object proximity measure to detect outliers. More details here. | What is the best way to identify outliers in multivariate data?
It may be an overshoot, but you may train an unsupervised Random Forest on the data and use the object proximity measure to detect outliers. More details here. | What is the best way to identify outliers in multivariate data?
It may be an overshoot, but you may train an unsupervised Random Forest on the data and use the object proximity measure to detect outliers. More details here. |
1,924 | What is the best way to identify outliers in multivariate data? | For moderate dimensions, like 3, then some sort of kernel cross-validation technique as suggested elsewhere seems reasonable and is the best I can come up with.
For higher dimensions, I'm not sure that the problem is solvable; it lands pretty squarely into 'curse-of-dimensionality' territory. The issue is that distanc... | What is the best way to identify outliers in multivariate data? | For moderate dimensions, like 3, then some sort of kernel cross-validation technique as suggested elsewhere seems reasonable and is the best I can come up with.
For higher dimensions, I'm not sure tha | What is the best way to identify outliers in multivariate data?
For moderate dimensions, like 3, then some sort of kernel cross-validation technique as suggested elsewhere seems reasonable and is the best I can come up with.
For higher dimensions, I'm not sure that the problem is solvable; it lands pretty squarely into... | What is the best way to identify outliers in multivariate data?
For moderate dimensions, like 3, then some sort of kernel cross-validation technique as suggested elsewhere seems reasonable and is the best I can come up with.
For higher dimensions, I'm not sure tha |
1,925 | What is the best way to identify outliers in multivariate data? | I'm not sure what you mean when you say you aren't thinking of a regression problem but of "true multivariate data". My initial response would be to calculate the Mahalanobis distance since it doesn't require that you specify a particular IV or DV, but at its core (as far as I understand it) it is related to a leverag... | What is the best way to identify outliers in multivariate data? | I'm not sure what you mean when you say you aren't thinking of a regression problem but of "true multivariate data". My initial response would be to calculate the Mahalanobis distance since it doesn' | What is the best way to identify outliers in multivariate data?
I'm not sure what you mean when you say you aren't thinking of a regression problem but of "true multivariate data". My initial response would be to calculate the Mahalanobis distance since it doesn't require that you specify a particular IV or DV, but at... | What is the best way to identify outliers in multivariate data?
I'm not sure what you mean when you say you aren't thinking of a regression problem but of "true multivariate data". My initial response would be to calculate the Mahalanobis distance since it doesn' |
1,926 | What is the best way to identify outliers in multivariate data? | I'm not aware that anyone is doing this, but I generally like to try dimensionality reduction when I have a problem like this. You might look into a method from manifold learning or non-linear dimensionality reduction.
An example would be a Kohonen map. A good reference for R is "Self- and Super-organizing Maps in R:... | What is the best way to identify outliers in multivariate data? | I'm not aware that anyone is doing this, but I generally like to try dimensionality reduction when I have a problem like this. You might look into a method from manifold learning or non-linear dimens | What is the best way to identify outliers in multivariate data?
I'm not aware that anyone is doing this, but I generally like to try dimensionality reduction when I have a problem like this. You might look into a method from manifold learning or non-linear dimensionality reduction.
An example would be a Kohonen map. ... | What is the best way to identify outliers in multivariate data?
I'm not aware that anyone is doing this, but I generally like to try dimensionality reduction when I have a problem like this. You might look into a method from manifold learning or non-linear dimens |
1,927 | What is the best way to identify outliers in multivariate data? | My first response would be that if you can do multivariate regression on the data, then to use the residuals from that regression to spot outliers. (I know you said it's not a regression problem, so this might not help you, sorry !)
I'm copying some of this from a Stackoverflow question I've previously answered which h... | What is the best way to identify outliers in multivariate data? | My first response would be that if you can do multivariate regression on the data, then to use the residuals from that regression to spot outliers. (I know you said it's not a regression problem, so t | What is the best way to identify outliers in multivariate data?
My first response would be that if you can do multivariate regression on the data, then to use the residuals from that regression to spot outliers. (I know you said it's not a regression problem, so this might not help you, sorry !)
I'm copying some of thi... | What is the best way to identify outliers in multivariate data?
My first response would be that if you can do multivariate regression on the data, then to use the residuals from that regression to spot outliers. (I know you said it's not a regression problem, so t |
1,928 | What is the best way to identify outliers in multivariate data? | One of the above answers touched in mahalanobis distances.... perhaps anpther step further and calculating simultaneous confidence intervals would help detect outliers! | What is the best way to identify outliers in multivariate data? | One of the above answers touched in mahalanobis distances.... perhaps anpther step further and calculating simultaneous confidence intervals would help detect outliers! | What is the best way to identify outliers in multivariate data?
One of the above answers touched in mahalanobis distances.... perhaps anpther step further and calculating simultaneous confidence intervals would help detect outliers! | What is the best way to identify outliers in multivariate data?
One of the above answers touched in mahalanobis distances.... perhaps anpther step further and calculating simultaneous confidence intervals would help detect outliers! |
1,929 | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression? | As an economist, the analysis of variance (ANOVA) is taught and usually understood in relation to linear regression (e.g. in Arthur Goldberger's A Course in Econometrics). Economists/Econometricians typically view ANOVA as uninteresting and prefer to move straight to regression models. From the perspective of linear (o... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio | As an economist, the analysis of variance (ANOVA) is taught and usually understood in relation to linear regression (e.g. in Arthur Goldberger's A Course in Econometrics). Economists/Econometricians t | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression?
As an economist, the analysis of variance (ANOVA) is taught and usually understood in relation to linear regression (e.g. in Arthur Goldberger's A Course in Econometrics). Economists/Econometricians typically view ANO... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio
As an economist, the analysis of variance (ANOVA) is taught and usually understood in relation to linear regression (e.g. in Arthur Goldberger's A Course in Econometrics). Economists/Econometricians t |
1,930 | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression? | I think Graham's second paragraph gets at the heart of the matter. I suspect it's not so much technical than historical, probably due to the influence of "Statistical Methods for Research Workers", and the ease of teaching/applying the tool for non-statisticans in experimental analysis involving discrete factors, rath... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio | I think Graham's second paragraph gets at the heart of the matter. I suspect it's not so much technical than historical, probably due to the influence of "Statistical Methods for Research Workers", a | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression?
I think Graham's second paragraph gets at the heart of the matter. I suspect it's not so much technical than historical, probably due to the influence of "Statistical Methods for Research Workers", and the ease of te... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio
I think Graham's second paragraph gets at the heart of the matter. I suspect it's not so much technical than historical, probably due to the influence of "Statistical Methods for Research Workers", a |
1,931 | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression? | I would say that some of you are using the term regression when you should be using general linear model. I think of regression as a glm that involves continuous covariates. When continuous covariates are combined with dummy variables that should be called analysis of covariance. If only dummy variables are used we ... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio | I would say that some of you are using the term regression when you should be using general linear model. I think of regression as a glm that involves continuous covariates. When continuous covariat | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression?
I would say that some of you are using the term regression when you should be using general linear model. I think of regression as a glm that involves continuous covariates. When continuous covariates are combined w... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio
I would say that some of you are using the term regression when you should be using general linear model. I think of regression as a glm that involves continuous covariates. When continuous covariat |
1,932 | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression? | ANOVA can be used with categorical explanatory variables (factors) that take more than 2 values (levels), and gives a basic test that the mean response is the same for every value. This avoids the regression problem on carrying multiple pairwise t-tests between those levels:
Multiple t-tests on a fixed 5% significance... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio | ANOVA can be used with categorical explanatory variables (factors) that take more than 2 values (levels), and gives a basic test that the mean response is the same for every value. This avoids the reg | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression?
ANOVA can be used with categorical explanatory variables (factors) that take more than 2 values (levels), and gives a basic test that the mean response is the same for every value. This avoids the regression problem o... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio
ANOVA can be used with categorical explanatory variables (factors) that take more than 2 values (levels), and gives a basic test that the mean response is the same for every value. This avoids the reg |
1,933 | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression? | ANOVA you are testing whether there are significant difference between the population means assuming you are comparing more than two population means, then you are going to use an F test.
In regression analysis you build a model between independent variables and a dependent variable. If you have one independent variab... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio | ANOVA you are testing whether there are significant difference between the population means assuming you are comparing more than two population means, then you are going to use an F test.
In regressi | Why is ANOVA taught / used as if it is a different research methodology compared to linear regression?
ANOVA you are testing whether there are significant difference between the population means assuming you are comparing more than two population means, then you are going to use an F test.
In regression analysis you b... | Why is ANOVA taught / used as if it is a different research methodology compared to linear regressio
ANOVA you are testing whether there are significant difference between the population means assuming you are comparing more than two population means, then you are going to use an F test.
In regressi |
1,934 | On the importance of the i.i.d. assumption in statistical learning | The i.i.d. assumption about the pairs $(\mathbf{X}_i, y_i)$, $i = 1, \ldots, N$, is often made in statistics and in machine learning. Sometimes for a good reason, sometimes out of convenience and sometimes just because we usually make this assumption. To satisfactorily answer if the assumption is really necessary, and ... | On the importance of the i.i.d. assumption in statistical learning | The i.i.d. assumption about the pairs $(\mathbf{X}_i, y_i)$, $i = 1, \ldots, N$, is often made in statistics and in machine learning. Sometimes for a good reason, sometimes out of convenience and some | On the importance of the i.i.d. assumption in statistical learning
The i.i.d. assumption about the pairs $(\mathbf{X}_i, y_i)$, $i = 1, \ldots, N$, is often made in statistics and in machine learning. Sometimes for a good reason, sometimes out of convenience and sometimes just because we usually make this assumption. T... | On the importance of the i.i.d. assumption in statistical learning
The i.i.d. assumption about the pairs $(\mathbf{X}_i, y_i)$, $i = 1, \ldots, N$, is often made in statistics and in machine learning. Sometimes for a good reason, sometimes out of convenience and some |
1,935 | On the importance of the i.i.d. assumption in statistical learning | What i.i.d. assumption states is that random variables are independent and identically distributed. You can formally define what does it mean, but informally it says that all the variables provide the same kind of information independently of each other (you can read also about related exchangeability).
From the abstra... | On the importance of the i.i.d. assumption in statistical learning | What i.i.d. assumption states is that random variables are independent and identically distributed. You can formally define what does it mean, but informally it says that all the variables provide the | On the importance of the i.i.d. assumption in statistical learning
What i.i.d. assumption states is that random variables are independent and identically distributed. You can formally define what does it mean, but informally it says that all the variables provide the same kind of information independently of each other... | On the importance of the i.i.d. assumption in statistical learning
What i.i.d. assumption states is that random variables are independent and identically distributed. You can formally define what does it mean, but informally it says that all the variables provide the |
1,936 | On the importance of the i.i.d. assumption in statistical learning | In my opinion there are two rather mundane reasons why the i.i.d. assumption is important in statistical learning (or statistics in general).
Lots of behind the scenes mathematics depend on this assumption. If you want to prove that your learning method actually works for more than one data set, i.i.d. assumption will... | On the importance of the i.i.d. assumption in statistical learning | In my opinion there are two rather mundane reasons why the i.i.d. assumption is important in statistical learning (or statistics in general).
Lots of behind the scenes mathematics depend on this assu | On the importance of the i.i.d. assumption in statistical learning
In my opinion there are two rather mundane reasons why the i.i.d. assumption is important in statistical learning (or statistics in general).
Lots of behind the scenes mathematics depend on this assumption. If you want to prove that your learning metho... | On the importance of the i.i.d. assumption in statistical learning
In my opinion there are two rather mundane reasons why the i.i.d. assumption is important in statistical learning (or statistics in general).
Lots of behind the scenes mathematics depend on this assu |
1,937 | On the importance of the i.i.d. assumption in statistical learning | The only place where one can safely ignored iid is in undergraduate statistics and machine learning courses. You have written that:
one can work around the i.i.d. assumption and obtain robust results. Actually the results will usually stay the same, it is rather the inferences that one can draw that will change...
Th... | On the importance of the i.i.d. assumption in statistical learning | The only place where one can safely ignored iid is in undergraduate statistics and machine learning courses. You have written that:
one can work around the i.i.d. assumption and obtain robust results | On the importance of the i.i.d. assumption in statistical learning
The only place where one can safely ignored iid is in undergraduate statistics and machine learning courses. You have written that:
one can work around the i.i.d. assumption and obtain robust results. Actually the results will usually stay the same, it... | On the importance of the i.i.d. assumption in statistical learning
The only place where one can safely ignored iid is in undergraduate statistics and machine learning courses. You have written that:
one can work around the i.i.d. assumption and obtain robust results |
1,938 | On the importance of the i.i.d. assumption in statistical learning | I would like to stress that in some circumstances, the data are not i.i.d. and statistical learning is still possible. It is crucial to have an identifiable model for the joint distribution of all observations; if the observations are i.i.d. then this joint distribution is easily obtained from the marginal distribution... | On the importance of the i.i.d. assumption in statistical learning | I would like to stress that in some circumstances, the data are not i.i.d. and statistical learning is still possible. It is crucial to have an identifiable model for the joint distribution of all obs | On the importance of the i.i.d. assumption in statistical learning
I would like to stress that in some circumstances, the data are not i.i.d. and statistical learning is still possible. It is crucial to have an identifiable model for the joint distribution of all observations; if the observations are i.i.d. then this j... | On the importance of the i.i.d. assumption in statistical learning
I would like to stress that in some circumstances, the data are not i.i.d. and statistical learning is still possible. It is crucial to have an identifiable model for the joint distribution of all obs |
1,939 | On the importance of the i.i.d. assumption in statistical learning | One area where i.i.d. assumption is critical in practice (other that inference) is data collection. If you do not collect data in a random manner then you will have a sampling bias and your data will not be a good representation of the underlying model. | On the importance of the i.i.d. assumption in statistical learning | One area where i.i.d. assumption is critical in practice (other that inference) is data collection. If you do not collect data in a random manner then you will have a sampling bias and your data will | On the importance of the i.i.d. assumption in statistical learning
One area where i.i.d. assumption is critical in practice (other that inference) is data collection. If you do not collect data in a random manner then you will have a sampling bias and your data will not be a good representation of the underlying model. | On the importance of the i.i.d. assumption in statistical learning
One area where i.i.d. assumption is critical in practice (other that inference) is data collection. If you do not collect data in a random manner then you will have a sampling bias and your data will |
1,940 | Is there a way to remember the definitions of Type I and Type II Errors? | Since type two means "False negative" or sort of "false false", I remember it as the number of falses.
Type I: "I falsely think the alternate hypothesis is true" (one false)
Type II: "I falsely think the alternate hypothesis is false" (two falses) | Is there a way to remember the definitions of Type I and Type II Errors? | Since type two means "False negative" or sort of "false false", I remember it as the number of falses.
Type I: "I falsely think the alternate hypothesis is true" (one false)
Type II: "I falsely thin | Is there a way to remember the definitions of Type I and Type II Errors?
Since type two means "False negative" or sort of "false false", I remember it as the number of falses.
Type I: "I falsely think the alternate hypothesis is true" (one false)
Type II: "I falsely think the alternate hypothesis is false" (two false... | Is there a way to remember the definitions of Type I and Type II Errors?
Since type two means "False negative" or sort of "false false", I remember it as the number of falses.
Type I: "I falsely think the alternate hypothesis is true" (one false)
Type II: "I falsely thin |
1,941 | Is there a way to remember the definitions of Type I and Type II Errors? | When the boy cried wolf ...
The first error the villagers made (when they believed him) was a type 1 error.
The second error the villagers made (when they didn't believe him) was a type 2 error.
The boy's cry was an alternative hypothesis because the null hypothesis is no wolf ;) | Is there a way to remember the definitions of Type I and Type II Errors? | When the boy cried wolf ...
The first error the villagers made (when they believed him) was a type 1 error.
The second error the villagers made (when they didn't believe him) was a type 2 error.
The | Is there a way to remember the definitions of Type I and Type II Errors?
When the boy cried wolf ...
The first error the villagers made (when they believed him) was a type 1 error.
The second error the villagers made (when they didn't believe him) was a type 2 error.
The boy's cry was an alternative hypothesis because... | Is there a way to remember the definitions of Type I and Type II Errors?
When the boy cried wolf ...
The first error the villagers made (when they believed him) was a type 1 error.
The second error the villagers made (when they didn't believe him) was a type 2 error.
The |
1,942 | Is there a way to remember the definitions of Type I and Type II Errors? | I make no apologies for posting such a ridiculous image, because that's exactly why it's easy to remember. Null hypothesis: Patient is not pregnant.
Image source: Ellis, P.D. (2010), “Effect Size FAQs,” website http://www.effectsizefaq.com, accessed on 12/18/2014. | Is there a way to remember the definitions of Type I and Type II Errors? | I make no apologies for posting such a ridiculous image, because that's exactly why it's easy to remember. Null hypothesis: Patient is not pregnant.
Image source: Ellis, P.D. (2010), “Effect Size FAQ | Is there a way to remember the definitions of Type I and Type II Errors?
I make no apologies for posting such a ridiculous image, because that's exactly why it's easy to remember. Null hypothesis: Patient is not pregnant.
Image source: Ellis, P.D. (2010), “Effect Size FAQs,” website http://www.effectsizefaq.com, acces... | Is there a way to remember the definitions of Type I and Type II Errors?
I make no apologies for posting such a ridiculous image, because that's exactly why it's easy to remember. Null hypothesis: Patient is not pregnant.
Image source: Ellis, P.D. (2010), “Effect Size FAQ |
1,943 | Is there a way to remember the definitions of Type I and Type II Errors? | Here's a handy way that happens to have some truth to it.
Young scientists commit Type-I because they want to find effects and jump the gun while old scientist commit Type-II because they refuse to change their beliefs.
(someone comment in a funnier version of that :) ) | Is there a way to remember the definitions of Type I and Type II Errors? | Here's a handy way that happens to have some truth to it.
Young scientists commit Type-I because they want to find effects and jump the gun while old scientist commit Type-II because they refuse to ch | Is there a way to remember the definitions of Type I and Type II Errors?
Here's a handy way that happens to have some truth to it.
Young scientists commit Type-I because they want to find effects and jump the gun while old scientist commit Type-II because they refuse to change their beliefs.
(someone comment in a funni... | Is there a way to remember the definitions of Type I and Type II Errors?
Here's a handy way that happens to have some truth to it.
Young scientists commit Type-I because they want to find effects and jump the gun while old scientist commit Type-II because they refuse to ch |
1,944 | Is there a way to remember the definitions of Type I and Type II Errors? | I was talking to a friend of mine about this and he kicked me a link to the Wikipedia article on type I and type II errors, where they apparently now provide a (somewhat unhelpful, in my opinion) mnemonic. I did, however, want to add it here just for the sake of completion. Although I didn't think it helped me, it migh... | Is there a way to remember the definitions of Type I and Type II Errors? | I was talking to a friend of mine about this and he kicked me a link to the Wikipedia article on type I and type II errors, where they apparently now provide a (somewhat unhelpful, in my opinion) mnem | Is there a way to remember the definitions of Type I and Type II Errors?
I was talking to a friend of mine about this and he kicked me a link to the Wikipedia article on type I and type II errors, where they apparently now provide a (somewhat unhelpful, in my opinion) mnemonic. I did, however, want to add it here just ... | Is there a way to remember the definitions of Type I and Type II Errors?
I was talking to a friend of mine about this and he kicked me a link to the Wikipedia article on type I and type II errors, where they apparently now provide a (somewhat unhelpful, in my opinion) mnem |
1,945 | Is there a way to remember the definitions of Type I and Type II Errors? | You could reject the idea entirely.
Some authors (Andrew Gelman is one) are shifting to discussing Type S (sign) and Type M (magnitude) errors. You can infer the wrong effect direction (e.g., you believe the treatment group does better but actually does worse) or the wrong magnitude (e.g., you find a massive effect wh... | Is there a way to remember the definitions of Type I and Type II Errors? | You could reject the idea entirely.
Some authors (Andrew Gelman is one) are shifting to discussing Type S (sign) and Type M (magnitude) errors. You can infer the wrong effect direction (e.g., you bel | Is there a way to remember the definitions of Type I and Type II Errors?
You could reject the idea entirely.
Some authors (Andrew Gelman is one) are shifting to discussing Type S (sign) and Type M (magnitude) errors. You can infer the wrong effect direction (e.g., you believe the treatment group does better but actual... | Is there a way to remember the definitions of Type I and Type II Errors?
You could reject the idea entirely.
Some authors (Andrew Gelman is one) are shifting to discussing Type S (sign) and Type M (magnitude) errors. You can infer the wrong effect direction (e.g., you bel |
1,946 | Is there a way to remember the definitions of Type I and Type II Errors? | I'll try not to be redundant with other responses (although it seems a little bit what J. M. already suggested), but I generally like showing the following two pictures: | Is there a way to remember the definitions of Type I and Type II Errors? | I'll try not to be redundant with other responses (although it seems a little bit what J. M. already suggested), but I generally like showing the following two pictures: | Is there a way to remember the definitions of Type I and Type II Errors?
I'll try not to be redundant with other responses (although it seems a little bit what J. M. already suggested), but I generally like showing the following two pictures: | Is there a way to remember the definitions of Type I and Type II Errors?
I'll try not to be redundant with other responses (although it seems a little bit what J. M. already suggested), but I generally like showing the following two pictures: |
1,947 | Is there a way to remember the definitions of Type I and Type II Errors? | I use the "judicial" approach for remembering the difference between type I and type II: a judge committing a type I error sends an innocent man to jail, while a judge committing a type II error lets a guilty man walk free. | Is there a way to remember the definitions of Type I and Type II Errors? | I use the "judicial" approach for remembering the difference between type I and type II: a judge committing a type I error sends an innocent man to jail, while a judge committing a type II error lets | Is there a way to remember the definitions of Type I and Type II Errors?
I use the "judicial" approach for remembering the difference between type I and type II: a judge committing a type I error sends an innocent man to jail, while a judge committing a type II error lets a guilty man walk free. | Is there a way to remember the definitions of Type I and Type II Errors?
I use the "judicial" approach for remembering the difference between type I and type II: a judge committing a type I error sends an innocent man to jail, while a judge committing a type II error lets |
1,948 | Is there a way to remember the definitions of Type I and Type II Errors? | Based on the principle of Occam's razor, Type I errors (rejecting the null hypothesis when it is true) are "arguably" worse than Type II errors (not rejecting the null hypothesis when it is false).
If you believe such an argument:
Type I errors are of primary concern
Type II errors are of secondary concern
Note: I'm ... | Is there a way to remember the definitions of Type I and Type II Errors? | Based on the principle of Occam's razor, Type I errors (rejecting the null hypothesis when it is true) are "arguably" worse than Type II errors (not rejecting the null hypothesis when it is false).
If | Is there a way to remember the definitions of Type I and Type II Errors?
Based on the principle of Occam's razor, Type I errors (rejecting the null hypothesis when it is true) are "arguably" worse than Type II errors (not rejecting the null hypothesis when it is false).
If you believe such an argument:
Type I errors a... | Is there a way to remember the definitions of Type I and Type II Errors?
Based on the principle of Occam's razor, Type I errors (rejecting the null hypothesis when it is true) are "arguably" worse than Type II errors (not rejecting the null hypothesis when it is false).
If |
1,949 | Is there a way to remember the definitions of Type I and Type II Errors? | Here is one explanation that might help you remember the difference.
TYPE I ERROR: An alarm without a fire.
TYPE II ERROR: A fire without an alarm.
Every cook knows how to avoid Type I Error - just remove the batteries. Unfortunately, this increases the incidences of Type II error. :)
Reducing the chances of Type II er... | Is there a way to remember the definitions of Type I and Type II Errors? | Here is one explanation that might help you remember the difference.
TYPE I ERROR: An alarm without a fire.
TYPE II ERROR: A fire without an alarm.
Every cook knows how to avoid Type I Error - just re | Is there a way to remember the definitions of Type I and Type II Errors?
Here is one explanation that might help you remember the difference.
TYPE I ERROR: An alarm without a fire.
TYPE II ERROR: A fire without an alarm.
Every cook knows how to avoid Type I Error - just remove the batteries. Unfortunately, this increas... | Is there a way to remember the definitions of Type I and Type II Errors?
Here is one explanation that might help you remember the difference.
TYPE I ERROR: An alarm without a fire.
TYPE II ERROR: A fire without an alarm.
Every cook knows how to avoid Type I Error - just re |
1,950 | Is there a way to remember the definitions of Type I and Type II Errors? | Hurrah, a question non-technical enough so as I can answer it!
"Type one is a con" [rhyming]- i.e. fools you into thinking that a difference exists when it doesn't. Always works for me. | Is there a way to remember the definitions of Type I and Type II Errors? | Hurrah, a question non-technical enough so as I can answer it!
"Type one is a con" [rhyming]- i.e. fools you into thinking that a difference exists when it doesn't. Always works for me. | Is there a way to remember the definitions of Type I and Type II Errors?
Hurrah, a question non-technical enough so as I can answer it!
"Type one is a con" [rhyming]- i.e. fools you into thinking that a difference exists when it doesn't. Always works for me. | Is there a way to remember the definitions of Type I and Type II Errors?
Hurrah, a question non-technical enough so as I can answer it!
"Type one is a con" [rhyming]- i.e. fools you into thinking that a difference exists when it doesn't. Always works for me. |
1,951 | Is there a way to remember the definitions of Type I and Type II Errors? | (a bit joke answer I invented just a minute ago)
A first class person thinks he is always right.
A second class person thinks he is always wrong.
The first class person can only make a type I error (because sometimes he will be wrong).
The second class person can only make a type II error (because sometimes he will... | Is there a way to remember the definitions of Type I and Type II Errors? | (a bit joke answer I invented just a minute ago)
A first class person thinks he is always right.
A second class person thinks he is always wrong.
The first class person can only make a type I erro | Is there a way to remember the definitions of Type I and Type II Errors?
(a bit joke answer I invented just a minute ago)
A first class person thinks he is always right.
A second class person thinks he is always wrong.
The first class person can only make a type I error (because sometimes he will be wrong).
The sec... | Is there a way to remember the definitions of Type I and Type II Errors?
(a bit joke answer I invented just a minute ago)
A first class person thinks he is always right.
A second class person thinks he is always wrong.
The first class person can only make a type I erro |
1,952 | Is there a way to remember the definitions of Type I and Type II Errors? | I used to think of it in terms of the usual picture of two Normal distributions (or bell curves). Going left to right, distribution 1 is the Null, and the distribution 2 is the Alternative. Type I (erroneously) rejects the first (Null) and Type II "rejects" the second (Alternative).
(Now you just need to remember t... | Is there a way to remember the definitions of Type I and Type II Errors? | I used to think of it in terms of the usual picture of two Normal distributions (or bell curves). Going left to right, distribution 1 is the Null, and the distribution 2 is the Alternative. Type I ( | Is there a way to remember the definitions of Type I and Type II Errors?
I used to think of it in terms of the usual picture of two Normal distributions (or bell curves). Going left to right, distribution 1 is the Null, and the distribution 2 is the Alternative. Type I (erroneously) rejects the first (Null) and Type ... | Is there a way to remember the definitions of Type I and Type II Errors?
I used to think of it in terms of the usual picture of two Normal distributions (or bell curves). Going left to right, distribution 1 is the Null, and the distribution 2 is the Alternative. Type I ( |
1,953 | Is there a way to remember the definitions of Type I and Type II Errors? | My friend came up with this and I thought it was rather brilliant. She said that during the last two presidencies Republicans have committed both errors:
President ONE was Bush who commited a type ONE error by saying there were weapons of mass destruction in Iraq when in fact.....
Under president TWO, Obama, (some) Rep... | Is there a way to remember the definitions of Type I and Type II Errors? | My friend came up with this and I thought it was rather brilliant. She said that during the last two presidencies Republicans have committed both errors:
President ONE was Bush who commited a type ONE | Is there a way to remember the definitions of Type I and Type II Errors?
My friend came up with this and I thought it was rather brilliant. She said that during the last two presidencies Republicans have committed both errors:
President ONE was Bush who commited a type ONE error by saying there were weapons of mass des... | Is there a way to remember the definitions of Type I and Type II Errors?
My friend came up with this and I thought it was rather brilliant. She said that during the last two presidencies Republicans have committed both errors:
President ONE was Bush who commited a type ONE |
1,954 | Is there a way to remember the definitions of Type I and Type II Errors? | I am surprised that noone has suggested the 'art/baf' mnemonic. Basically remember that $\alpha$ is the probability of the type I error and $\beta$ is the probability of a type II error (this is easy to remember because $\alpha$ is the 1st letter in the greek alphabet, so goes with the 1st error, $\beta$ is the 2nd le... | Is there a way to remember the definitions of Type I and Type II Errors? | I am surprised that noone has suggested the 'art/baf' mnemonic. Basically remember that $\alpha$ is the probability of the type I error and $\beta$ is the probability of a type II error (this is easy | Is there a way to remember the definitions of Type I and Type II Errors?
I am surprised that noone has suggested the 'art/baf' mnemonic. Basically remember that $\alpha$ is the probability of the type I error and $\beta$ is the probability of a type II error (this is easy to remember because $\alpha$ is the 1st letter... | Is there a way to remember the definitions of Type I and Type II Errors?
I am surprised that noone has suggested the 'art/baf' mnemonic. Basically remember that $\alpha$ is the probability of the type I error and $\beta$ is the probability of a type II error (this is easy |
1,955 | Is there a way to remember the definitions of Type I and Type II Errors? | Type 1 = Reject : this is a ONE-word expression
Type 2 = Do not : this is a TWO-word expression | Is there a way to remember the definitions of Type I and Type II Errors? | Type 1 = Reject : this is a ONE-word expression
Type 2 = Do not : this is a TWO-word expression | Is there a way to remember the definitions of Type I and Type II Errors?
Type 1 = Reject : this is a ONE-word expression
Type 2 = Do not : this is a TWO-word expression | Is there a way to remember the definitions of Type I and Type II Errors?
Type 1 = Reject : this is a ONE-word expression
Type 2 = Do not : this is a TWO-word expression |
1,956 | Is there a way to remember the definitions of Type I and Type II Errors? | RAAR 'like a lion'= first part is *R*eject when we should *A*ccept (type I error)
second part is *A*ccept when we should *R*eject (type II error)
This is the easiest way to remember it for me :)
Good LUCK! | Is there a way to remember the definitions of Type I and Type II Errors? | RAAR 'like a lion'= first part is *R*eject when we should *A*ccept (type I error)
second part is *A*ccept when we should *R*eject (type II error)
This is the easiest way to remember it for me :)
Good | Is there a way to remember the definitions of Type I and Type II Errors?
RAAR 'like a lion'= first part is *R*eject when we should *A*ccept (type I error)
second part is *A*ccept when we should *R*eject (type II error)
This is the easiest way to remember it for me :)
Good LUCK! | Is there a way to remember the definitions of Type I and Type II Errors?
RAAR 'like a lion'= first part is *R*eject when we should *A*ccept (type I error)
second part is *A*ccept when we should *R*eject (type II error)
This is the easiest way to remember it for me :)
Good |
1,957 | Is there a way to remember the definitions of Type I and Type II Errors? | I remember it by thinking: What's the first thing I do when I do a null-hypothesis significance test? I set the criterion for the probability that I will make a false rejection. Thus, type 1 is this criterion and type 2 is the other probability of interest: the probability that I will fail to reject the null when the n... | Is there a way to remember the definitions of Type I and Type II Errors? | I remember it by thinking: What's the first thing I do when I do a null-hypothesis significance test? I set the criterion for the probability that I will make a false rejection. Thus, type 1 is this c | Is there a way to remember the definitions of Type I and Type II Errors?
I remember it by thinking: What's the first thing I do when I do a null-hypothesis significance test? I set the criterion for the probability that I will make a false rejection. Thus, type 1 is this criterion and type 2 is the other probability of... | Is there a way to remember the definitions of Type I and Type II Errors?
I remember it by thinking: What's the first thing I do when I do a null-hypothesis significance test? I set the criterion for the probability that I will make a false rejection. Thus, type 1 is this c |
1,958 | Is there a way to remember the definitions of Type I and Type II Errors? | Here's how I do it:
Type I is an Optimistic error.
Type II is a Pessimistic error.
O, P: 1, 2. They're alphabetical. | Is there a way to remember the definitions of Type I and Type II Errors? | Here's how I do it:
Type I is an Optimistic error.
Type II is a Pessimistic error.
O, P: 1, 2. They're alphabetical. | Is there a way to remember the definitions of Type I and Type II Errors?
Here's how I do it:
Type I is an Optimistic error.
Type II is a Pessimistic error.
O, P: 1, 2. They're alphabetical. | Is there a way to remember the definitions of Type I and Type II Errors?
Here's how I do it:
Type I is an Optimistic error.
Type II is a Pessimistic error.
O, P: 1, 2. They're alphabetical. |
1,959 | Is there a way to remember the definitions of Type I and Type II Errors? | Memorize “It’s Type I not II where the null is true” as it rhymes and figure the rest out while you are looking at the problem
Since you are making an error
Type I - the null is true but you say it isn’t (reject it) - False positive
Then Type II is where the null is not True but you say it is (Fail to reject it)- False... | Is there a way to remember the definitions of Type I and Type II Errors? | Memorize “It’s Type I not II where the null is true” as it rhymes and figure the rest out while you are looking at the problem
Since you are making an error
Type I - the null is true but you say it is | Is there a way to remember the definitions of Type I and Type II Errors?
Memorize “It’s Type I not II where the null is true” as it rhymes and figure the rest out while you are looking at the problem
Since you are making an error
Type I - the null is true but you say it isn’t (reject it) - False positive
Then Type II i... | Is there a way to remember the definitions of Type I and Type II Errors?
Memorize “It’s Type I not II where the null is true” as it rhymes and figure the rest out while you are looking at the problem
Since you are making an error
Type I - the null is true but you say it is |
1,960 | Is there a way to remember the definitions of Type I and Type II Errors? | This is how I remember the difference between Type I and Type II errors
Type I is a false POSITIVE
Type II is a false NEGATIVE
Type I is so POSITIVE it jumps out of bed first, runs downstairs and finds a significant breakfast while Type II is so NEGATIVE it stays in bed all day so when it eventually crawls out all the ... | Is there a way to remember the definitions of Type I and Type II Errors? | This is how I remember the difference between Type I and Type II errors
Type I is a false POSITIVE
Type II is a false NEGATIVE
Type I is so POSITIVE it jumps out of bed first, runs downstairs and find | Is there a way to remember the definitions of Type I and Type II Errors?
This is how I remember the difference between Type I and Type II errors
Type I is a false POSITIVE
Type II is a false NEGATIVE
Type I is so POSITIVE it jumps out of bed first, runs downstairs and finds a significant breakfast while Type II is so N... | Is there a way to remember the definitions of Type I and Type II Errors?
This is how I remember the difference between Type I and Type II errors
Type I is a false POSITIVE
Type II is a false NEGATIVE
Type I is so POSITIVE it jumps out of bed first, runs downstairs and find |
1,961 | Is there a way to remember the definitions of Type I and Type II Errors? | Type One error Reject null hypothesis when it is true
T.O.E.R.N.H.W.I.I.T.
Tiny Overly Eager Raccoons Never Hide When It Is Teatime
Type Two Error Accept null hypothesis when it is false
T.T.E.A.N.H.W.I.I.F.
Twelve Tan Elvis's Ate Nine Hams With Intelligent Irish Farmers | Is there a way to remember the definitions of Type I and Type II Errors? | Type One error Reject null hypothesis when it is true
T.O.E.R.N.H.W.I.I.T.
Tiny Overly Eager Raccoons Never Hide When It Is Teatime
Type Two Error Accept null hypothesis when it is false
T.T.E.A.N | Is there a way to remember the definitions of Type I and Type II Errors?
Type One error Reject null hypothesis when it is true
T.O.E.R.N.H.W.I.I.T.
Tiny Overly Eager Raccoons Never Hide When It Is Teatime
Type Two Error Accept null hypothesis when it is false
T.T.E.A.N.H.W.I.I.F.
Twelve Tan Elvis's Ate Nine Hams Wi... | Is there a way to remember the definitions of Type I and Type II Errors?
Type One error Reject null hypothesis when it is true
T.O.E.R.N.H.W.I.I.T.
Tiny Overly Eager Raccoons Never Hide When It Is Teatime
Type Two Error Accept null hypothesis when it is false
T.T.E.A.N |
1,962 | Is there a way to remember the definitions of Type I and Type II Errors? | To a software engineer: How about associating Type I error (first of the two) with the term "S"erial "N"umber -- you find something "significant" but it's acutally "not." Type II error is just the opposite once you know what Type I error is. | Is there a way to remember the definitions of Type I and Type II Errors? | To a software engineer: How about associating Type I error (first of the two) with the term "S"erial "N"umber -- you find something "significant" but it's acutally "not." Type II error is just the op | Is there a way to remember the definitions of Type I and Type II Errors?
To a software engineer: How about associating Type I error (first of the two) with the term "S"erial "N"umber -- you find something "significant" but it's acutally "not." Type II error is just the opposite once you know what Type I error is. | Is there a way to remember the definitions of Type I and Type II Errors?
To a software engineer: How about associating Type I error (first of the two) with the term "S"erial "N"umber -- you find something "significant" but it's acutally "not." Type II error is just the op |
1,963 | Is there a way to remember the definitions of Type I and Type II Errors? | Sometimes reading really old scientific papers help me to understand some ideas behind statistics.
...they identified "two sources of error", namely:
(a) the error of rejecting a hypothesis that should have been accepted, and
(b) the error of accepting a hypothesis that should have been rejected.
(wiki)
Original source... | Is there a way to remember the definitions of Type I and Type II Errors? | Sometimes reading really old scientific papers help me to understand some ideas behind statistics.
...they identified "two sources of error", namely:
(a) the error of rejecting a hypothesis that shoul | Is there a way to remember the definitions of Type I and Type II Errors?
Sometimes reading really old scientific papers help me to understand some ideas behind statistics.
...they identified "two sources of error", namely:
(a) the error of rejecting a hypothesis that should have been accepted, and
(b) the error of acce... | Is there a way to remember the definitions of Type I and Type II Errors?
Sometimes reading really old scientific papers help me to understand some ideas behind statistics.
...they identified "two sources of error", namely:
(a) the error of rejecting a hypothesis that shoul |
1,964 | Is there a way to remember the definitions of Type I and Type II Errors? | I think that the usual table is confusing because it concatenates negation verbs. I found the following "verdict table" easier to remember an generalize:
H0 (fair)
True False
Positive False positive True positive
Decision Typ... | Is there a way to remember the definitions of Type I and Type II Errors? | I think that the usual table is confusing because it concatenates negation verbs. I found the following "verdict table" easier to remember an generalize:
H0 (fair)
| Is there a way to remember the definitions of Type I and Type II Errors?
I think that the usual table is confusing because it concatenates negation verbs. I found the following "verdict table" easier to remember an generalize:
H0 (fair)
True False
... | Is there a way to remember the definitions of Type I and Type II Errors?
I think that the usual table is confusing because it concatenates negation verbs. I found the following "verdict table" easier to remember an generalize:
H0 (fair)
|
1,965 | Is there a way to remember the definitions of Type I and Type II Errors? | RouTiNe FoR FuN
Type I error is RTN: Reject The Null
Type II error is FRFN: Fail to Reject a False Null (hypothesis) | Is there a way to remember the definitions of Type I and Type II Errors? | RouTiNe FoR FuN
Type I error is RTN: Reject The Null
Type II error is FRFN: Fail to Reject a False Null (hypothesis) | Is there a way to remember the definitions of Type I and Type II Errors?
RouTiNe FoR FuN
Type I error is RTN: Reject The Null
Type II error is FRFN: Fail to Reject a False Null (hypothesis) | Is there a way to remember the definitions of Type I and Type II Errors?
RouTiNe FoR FuN
Type I error is RTN: Reject The Null
Type II error is FRFN: Fail to Reject a False Null (hypothesis) |
1,966 | Is there a way to remember the definitions of Type I and Type II Errors? | My mnemonic for Type II errors is:
TWO: This Was Opposing [our chance of getting published/funding/famous], i.e., the experimental hypothesis was rejected (albeit in error).
Or
TWO: This Was Out-and-out failure (but it's an error so it's not).
Type I is what is left (i.e., false positive). | Is there a way to remember the definitions of Type I and Type II Errors? | My mnemonic for Type II errors is:
TWO: This Was Opposing [our chance of getting published/funding/famous], i.e., the experimental hypothesis was rejected (albeit in error).
Or
TWO: This Was Out-and-o | Is there a way to remember the definitions of Type I and Type II Errors?
My mnemonic for Type II errors is:
TWO: This Was Opposing [our chance of getting published/funding/famous], i.e., the experimental hypothesis was rejected (albeit in error).
Or
TWO: This Was Out-and-out failure (but it's an error so it's not).
Ty... | Is there a way to remember the definitions of Type I and Type II Errors?
My mnemonic for Type II errors is:
TWO: This Was Opposing [our chance of getting published/funding/famous], i.e., the experimental hypothesis was rejected (albeit in error).
Or
TWO: This Was Out-and-o |
1,967 | Is there a way to remember the definitions of Type I and Type II Errors? | After reading through all of these I came up with my own to remember about type I (making the opposite apply to type II.)
[A]lpha is first and is an error when you [A]ccept the [A]lternate. AAA. | Is there a way to remember the definitions of Type I and Type II Errors? | After reading through all of these I came up with my own to remember about type I (making the opposite apply to type II.)
[A]lpha is first and is an error when you [A]ccept the [A]lternate. AAA. | Is there a way to remember the definitions of Type I and Type II Errors?
After reading through all of these I came up with my own to remember about type I (making the opposite apply to type II.)
[A]lpha is first and is an error when you [A]ccept the [A]lternate. AAA. | Is there a way to remember the definitions of Type I and Type II Errors?
After reading through all of these I came up with my own to remember about type I (making the opposite apply to type II.)
[A]lpha is first and is an error when you [A]ccept the [A]lternate. AAA. |
1,968 | Is there a way to remember the definitions of Type I and Type II Errors? | RAT !RAF
RAT denotes type I errors and !RAF is type II.
Type I error - RAT
Rejecting H0 when it's Actually True
Type II - !RAF
! Rejecting H0 when it's Actually False ≡
not Rejecting H0 when it's Actually False
! denotes the not operator so replace ! with the word "not".
NB: H0 = Null hypothesis | Is there a way to remember the definitions of Type I and Type II Errors? | RAT !RAF
RAT denotes type I errors and !RAF is type II.
Type I error - RAT
Rejecting H0 when it's Actually True
Type II - !RAF
! Rejecting H0 when it's Actually False ≡
not Rejecting H0 when it's | Is there a way to remember the definitions of Type I and Type II Errors?
RAT !RAF
RAT denotes type I errors and !RAF is type II.
Type I error - RAT
Rejecting H0 when it's Actually True
Type II - !RAF
! Rejecting H0 when it's Actually False ≡
not Rejecting H0 when it's Actually False
! denotes the not operator so ... | Is there a way to remember the definitions of Type I and Type II Errors?
RAT !RAF
RAT denotes type I errors and !RAF is type II.
Type I error - RAT
Rejecting H0 when it's Actually True
Type II - !RAF
! Rejecting H0 when it's Actually False ≡
not Rejecting H0 when it's |
1,969 | Is there a way to remember the definitions of Type I and Type II Errors? | If the error is type I, the true null is done.
If the error is type II, a false null gets through. | Is there a way to remember the definitions of Type I and Type II Errors? | If the error is type I, the true null is done.
If the error is type II, a false null gets through. | Is there a way to remember the definitions of Type I and Type II Errors?
If the error is type I, the true null is done.
If the error is type II, a false null gets through. | Is there a way to remember the definitions of Type I and Type II Errors?
If the error is type I, the true null is done.
If the error is type II, a false null gets through. |
1,970 | The Book of Why by Judea Pearl: Why is he bashing statistics? | I fully agree that Pearl's tone is arrogant, and his characterisation of "statisticians" is simplistic and monolithic. Also, I don't find his writing particularly clear.
However, I think he has a point.
Causal reasoning was not part of my formal training (MSc): the closest I got to the topic was an elective course in ... | The Book of Why by Judea Pearl: Why is he bashing statistics? | I fully agree that Pearl's tone is arrogant, and his characterisation of "statisticians" is simplistic and monolithic. Also, I don't find his writing particularly clear.
However, I think he has a poin | The Book of Why by Judea Pearl: Why is he bashing statistics?
I fully agree that Pearl's tone is arrogant, and his characterisation of "statisticians" is simplistic and monolithic. Also, I don't find his writing particularly clear.
However, I think he has a point.
Causal reasoning was not part of my formal training (M... | The Book of Why by Judea Pearl: Why is he bashing statistics?
I fully agree that Pearl's tone is arrogant, and his characterisation of "statisticians" is simplistic and monolithic. Also, I don't find his writing particularly clear.
However, I think he has a poin |
1,971 | The Book of Why by Judea Pearl: Why is he bashing statistics? | Your very question reflects what Pearl is saying!
a simple linear regression is essentially a causal model
No, a linear regression is a statistical model, not a causal model. Let's assume $Y, X, Z$ are random variables with a multivariate normal distribution. Then you can correctly estimate the linear expectations $E... | The Book of Why by Judea Pearl: Why is he bashing statistics? | Your very question reflects what Pearl is saying!
a simple linear regression is essentially a causal model
No, a linear regression is a statistical model, not a causal model. Let's assume $Y, X, Z$ | The Book of Why by Judea Pearl: Why is he bashing statistics?
Your very question reflects what Pearl is saying!
a simple linear regression is essentially a causal model
No, a linear regression is a statistical model, not a causal model. Let's assume $Y, X, Z$ are random variables with a multivariate normal distributi... | The Book of Why by Judea Pearl: Why is he bashing statistics?
Your very question reflects what Pearl is saying!
a simple linear regression is essentially a causal model
No, a linear regression is a statistical model, not a causal model. Let's assume $Y, X, Z$ |
1,972 | The Book of Why by Judea Pearl: Why is he bashing statistics? | I'm a fan of Judea's writing, and I've read Causality (love) and Book of Why (like).
I do not feel that Judea is bashing statistics. It's hard to hear criticism. But what can we say about any person or field that doesn't take criticism? They tend from greatness to complacency. You must ask: is the criticism correct, ne... | The Book of Why by Judea Pearl: Why is he bashing statistics? | I'm a fan of Judea's writing, and I've read Causality (love) and Book of Why (like).
I do not feel that Judea is bashing statistics. It's hard to hear criticism. But what can we say about any person o | The Book of Why by Judea Pearl: Why is he bashing statistics?
I'm a fan of Judea's writing, and I've read Causality (love) and Book of Why (like).
I do not feel that Judea is bashing statistics. It's hard to hear criticism. But what can we say about any person or field that doesn't take criticism? They tend from greatn... | The Book of Why by Judea Pearl: Why is he bashing statistics?
I'm a fan of Judea's writing, and I've read Causality (love) and Book of Why (like).
I do not feel that Judea is bashing statistics. It's hard to hear criticism. But what can we say about any person o |
1,973 | The Book of Why by Judea Pearl: Why is he bashing statistics? | I haven't read this book, so I can only judge the particular quote you give. However, even on this basis, I agree with you that this seems extremely unfair to the statistical profession. I actually think that statisticians have always done a remarkably good job at stressing the distinction between statistical associa... | The Book of Why by Judea Pearl: Why is he bashing statistics? | I haven't read this book, so I can only judge the particular quote you give. However, even on this basis, I agree with you that this seems extremely unfair to the statistical profession. I actually | The Book of Why by Judea Pearl: Why is he bashing statistics?
I haven't read this book, so I can only judge the particular quote you give. However, even on this basis, I agree with you that this seems extremely unfair to the statistical profession. I actually think that statisticians have always done a remarkably goo... | The Book of Why by Judea Pearl: Why is he bashing statistics?
I haven't read this book, so I can only judge the particular quote you give. However, even on this basis, I agree with you that this seems extremely unfair to the statistical profession. I actually |
1,974 | The Book of Why by Judea Pearl: Why is he bashing statistics? | a simple linear regression is essentially a causal model
Here's an example I came up with where a linear regression model fails to be causal. Let's say a priori that a drug was taken at time 0 (t=0) and that it has no effect on the rate of heart attacks at t=1. Heart attacks at t=1 affect heart attacks at t=2 (i.e. pr... | The Book of Why by Judea Pearl: Why is he bashing statistics? | a simple linear regression is essentially a causal model
Here's an example I came up with where a linear regression model fails to be causal. Let's say a priori that a drug was taken at time 0 (t=0) | The Book of Why by Judea Pearl: Why is he bashing statistics?
a simple linear regression is essentially a causal model
Here's an example I came up with where a linear regression model fails to be causal. Let's say a priori that a drug was taken at time 0 (t=0) and that it has no effect on the rate of heart attacks at ... | The Book of Why by Judea Pearl: Why is he bashing statistics?
a simple linear regression is essentially a causal model
Here's an example I came up with where a linear regression model fails to be causal. Let's say a priori that a drug was taken at time 0 (t=0) |
1,975 | The Book of Why by Judea Pearl: Why is he bashing statistics? | Two papers, the second a classic, that help (I think) shed additional lights on Judea's points and this topic more generally. This comes from someone who has used SEM (which is correlation and regression) repeatedly and resonates with his critiques:
https://www.sciencedirect.com/science/article/pii/S0022103111001466
h... | The Book of Why by Judea Pearl: Why is he bashing statistics? | Two papers, the second a classic, that help (I think) shed additional lights on Judea's points and this topic more generally. This comes from someone who has used SEM (which is correlation and regress | The Book of Why by Judea Pearl: Why is he bashing statistics?
Two papers, the second a classic, that help (I think) shed additional lights on Judea's points and this topic more generally. This comes from someone who has used SEM (which is correlation and regression) repeatedly and resonates with his critiques:
https:/... | The Book of Why by Judea Pearl: Why is he bashing statistics?
Two papers, the second a classic, that help (I think) shed additional lights on Judea's points and this topic more generally. This comes from someone who has used SEM (which is correlation and regress |
1,976 | The Book of Why by Judea Pearl: Why is he bashing statistics? | "...since we are essentially assuming that one variable is the cause and another is the effect (hence correlation is different approach from regression modelling)..."
Regression modeling most definitely does NOT make this assumption.
"... and testing whether this causal relationship explains the observed patterns."
If... | The Book of Why by Judea Pearl: Why is he bashing statistics? | "...since we are essentially assuming that one variable is the cause and another is the effect (hence correlation is different approach from regression modelling)..."
Regression modeling most definite | The Book of Why by Judea Pearl: Why is he bashing statistics?
"...since we are essentially assuming that one variable is the cause and another is the effect (hence correlation is different approach from regression modelling)..."
Regression modeling most definitely does NOT make this assumption.
"... and testing whether... | The Book of Why by Judea Pearl: Why is he bashing statistics?
"...since we are essentially assuming that one variable is the cause and another is the effect (hence correlation is different approach from regression modelling)..."
Regression modeling most definite |
1,977 | Solving for regression parameters in closed-form vs gradient descent | Unless the closed form solution is extremely expensive to compute, it generally is the way to go when it is available. However,
For most nonlinear regression problems there is no closed form solution.
Even in linear regression (one of the few cases where a closed form solution is available), it may be impractical t... | Solving for regression parameters in closed-form vs gradient descent | Unless the closed form solution is extremely expensive to compute, it generally is the way to go when it is available. However,
For most nonlinear regression problems there is no closed form solutio | Solving for regression parameters in closed-form vs gradient descent
Unless the closed form solution is extremely expensive to compute, it generally is the way to go when it is available. However,
For most nonlinear regression problems there is no closed form solution.
Even in linear regression (one of the few case... | Solving for regression parameters in closed-form vs gradient descent
Unless the closed form solution is extremely expensive to compute, it generally is the way to go when it is available. However,
For most nonlinear regression problems there is no closed form solutio |
1,978 | Solving for regression parameters in closed-form vs gradient descent | UPDATE
For linear regression, it's a one step procedure, so iteration of any kind is not needed.
For logistic regression, the Newton-Raphson iterative approach uses the second partial derivatives of the objective function w.r.t. each coefficient, as well as the first partial derivatives, so it converges much faster tha... | Solving for regression parameters in closed-form vs gradient descent | UPDATE
For linear regression, it's a one step procedure, so iteration of any kind is not needed.
For logistic regression, the Newton-Raphson iterative approach uses the second partial derivatives of t | Solving for regression parameters in closed-form vs gradient descent
UPDATE
For linear regression, it's a one step procedure, so iteration of any kind is not needed.
For logistic regression, the Newton-Raphson iterative approach uses the second partial derivatives of the objective function w.r.t. each coefficient, as w... | Solving for regression parameters in closed-form vs gradient descent
UPDATE
For linear regression, it's a one step procedure, so iteration of any kind is not needed.
For logistic regression, the Newton-Raphson iterative approach uses the second partial derivatives of t |
1,979 | If mean is so sensitive, why use it in the first place? | In a sense, the mean is used because it is sensitive to the data. If the distribution happens to be symmetric and the tails are about like the normal distribution, the mean is a very efficient summary of central tendency. The median, while being robust and well-defined for any continuous distribution, is only $\frac{... | If mean is so sensitive, why use it in the first place? | In a sense, the mean is used because it is sensitive to the data. If the distribution happens to be symmetric and the tails are about like the normal distribution, the mean is a very efficient summar | If mean is so sensitive, why use it in the first place?
In a sense, the mean is used because it is sensitive to the data. If the distribution happens to be symmetric and the tails are about like the normal distribution, the mean is a very efficient summary of central tendency. The median, while being robust and well-... | If mean is so sensitive, why use it in the first place?
In a sense, the mean is used because it is sensitive to the data. If the distribution happens to be symmetric and the tails are about like the normal distribution, the mean is a very efficient summar |
1,980 | If mean is so sensitive, why use it in the first place? | Lots of great answers already, but, taking a step back and getting a little more basic, I'd say it's because the answer you get depends on the question you ask. The mean and median answer different questions - sometimes one is appropriate, sometimes the other.
It's simple to say that the median should be used when ther... | If mean is so sensitive, why use it in the first place? | Lots of great answers already, but, taking a step back and getting a little more basic, I'd say it's because the answer you get depends on the question you ask. The mean and median answer different qu | If mean is so sensitive, why use it in the first place?
Lots of great answers already, but, taking a step back and getting a little more basic, I'd say it's because the answer you get depends on the question you ask. The mean and median answer different questions - sometimes one is appropriate, sometimes the other.
It'... | If mean is so sensitive, why use it in the first place?
Lots of great answers already, but, taking a step back and getting a little more basic, I'd say it's because the answer you get depends on the question you ask. The mean and median answer different qu |
1,981 | If mean is so sensitive, why use it in the first place? | When a value is garbage for us we call it "outlier" and want analysis be robust to it (and prefer median); when that same value is attractive we call it "extreme" and want analysis be sensitive to it (and prefer mean). Dialectics ...
Mean reacts equally to a shift of value irrespective to where in the distribution the ... | If mean is so sensitive, why use it in the first place? | When a value is garbage for us we call it "outlier" and want analysis be robust to it (and prefer median); when that same value is attractive we call it "extreme" and want analysis be sensitive to it | If mean is so sensitive, why use it in the first place?
When a value is garbage for us we call it "outlier" and want analysis be robust to it (and prefer median); when that same value is attractive we call it "extreme" and want analysis be sensitive to it (and prefer mean). Dialectics ...
Mean reacts equally to a shift... | If mean is so sensitive, why use it in the first place?
When a value is garbage for us we call it "outlier" and want analysis be robust to it (and prefer median); when that same value is attractive we call it "extreme" and want analysis be sensitive to it |
1,982 | If mean is so sensitive, why use it in the first place? | There are a lot of answers to this question. Here's one that you probably won't see elsewhere so I'm including it here because I believe it's pertinent to the topic. People often believe that because the median is considered a robust measure with respect to outliers that it's also robust to most everything. In fact,... | If mean is so sensitive, why use it in the first place? | There are a lot of answers to this question. Here's one that you probably won't see elsewhere so I'm including it here because I believe it's pertinent to the topic. People often believe that becaus | If mean is so sensitive, why use it in the first place?
There are a lot of answers to this question. Here's one that you probably won't see elsewhere so I'm including it here because I believe it's pertinent to the topic. People often believe that because the median is considered a robust measure with respect to outl... | If mean is so sensitive, why use it in the first place?
There are a lot of answers to this question. Here's one that you probably won't see elsewhere so I'm including it here because I believe it's pertinent to the topic. People often believe that becaus |
1,983 | If mean is so sensitive, why use it in the first place? | From the mean it's easy to calculate the sum over all items, e.g. if you know the average income of the population and the size of the population, you can immediately calculate the total income of the entire population.
The mean is straightforward to calculate in O(n) time complexity. Calculating the median in linear t... | If mean is so sensitive, why use it in the first place? | From the mean it's easy to calculate the sum over all items, e.g. if you know the average income of the population and the size of the population, you can immediately calculate the total income of the | If mean is so sensitive, why use it in the first place?
From the mean it's easy to calculate the sum over all items, e.g. if you know the average income of the population and the size of the population, you can immediately calculate the total income of the entire population.
The mean is straightforward to calculate in ... | If mean is so sensitive, why use it in the first place?
From the mean it's easy to calculate the sum over all items, e.g. if you know the average income of the population and the size of the population, you can immediately calculate the total income of the |
1,984 | If mean is so sensitive, why use it in the first place? | "It is a known that median is resistant to outliers. If that is the case, when and why would we use the mean in the first place?"
In cases one knows there are no outliers, for example when one knows the data-generating process (for example in mathematical statistics).
One should point out the trivial, that, these two ... | If mean is so sensitive, why use it in the first place? | "It is a known that median is resistant to outliers. If that is the case, when and why would we use the mean in the first place?"
In cases one knows there are no outliers, for example when one knows t | If mean is so sensitive, why use it in the first place?
"It is a known that median is resistant to outliers. If that is the case, when and why would we use the mean in the first place?"
In cases one knows there are no outliers, for example when one knows the data-generating process (for example in mathematical statisti... | If mean is so sensitive, why use it in the first place?
"It is a known that median is resistant to outliers. If that is the case, when and why would we use the mean in the first place?"
In cases one knows there are no outliers, for example when one knows t |
1,985 | If mean is so sensitive, why use it in the first place? | If the concern is over the presence of outliers, there are some straight-forward ways to check your data.
Outliers, almost by definition, come into our data when something changes either in the process generating the data or in the process collecting the data. i.e. the data ceases to be homogeneous. If your data is not... | If mean is so sensitive, why use it in the first place? | If the concern is over the presence of outliers, there are some straight-forward ways to check your data.
Outliers, almost by definition, come into our data when something changes either in the proces | If mean is so sensitive, why use it in the first place?
If the concern is over the presence of outliers, there are some straight-forward ways to check your data.
Outliers, almost by definition, come into our data when something changes either in the process generating the data or in the process collecting the data. i.e... | If mean is so sensitive, why use it in the first place?
If the concern is over the presence of outliers, there are some straight-forward ways to check your data.
Outliers, almost by definition, come into our data when something changes either in the proces |
1,986 | If mean is so sensitive, why use it in the first place? | When might you want the mean?
Examples from finance:
Bond returns:
The median bond return will generally be a few percentage points.
The mean bond return might be low or high depending on the default rate and recovery in default. The median will ignore all this!
Good luck explaining to your investors, "I know our fun... | If mean is so sensitive, why use it in the first place? | When might you want the mean?
Examples from finance:
Bond returns:
The median bond return will generally be a few percentage points.
The mean bond return might be low or high depending on the defaul | If mean is so sensitive, why use it in the first place?
When might you want the mean?
Examples from finance:
Bond returns:
The median bond return will generally be a few percentage points.
The mean bond return might be low or high depending on the default rate and recovery in default. The median will ignore all this!... | If mean is so sensitive, why use it in the first place?
When might you want the mean?
Examples from finance:
Bond returns:
The median bond return will generally be a few percentage points.
The mean bond return might be low or high depending on the defaul |
1,987 | If mean is so sensitive, why use it in the first place? | We use the mean more than the median because it is additive, in two senses. (I am surprised that in 11 years, no one has really said this!)
If data on a population is broken down into data about men and data about women, then for example:
\begin{align}
\text{average overall height =} &\text{average height for men} * \... | If mean is so sensitive, why use it in the first place? | We use the mean more than the median because it is additive, in two senses. (I am surprised that in 11 years, no one has really said this!)
If data on a population is broken down into data about men | If mean is so sensitive, why use it in the first place?
We use the mean more than the median because it is additive, in two senses. (I am surprised that in 11 years, no one has really said this!)
If data on a population is broken down into data about men and data about women, then for example:
\begin{align}
\text{aver... | If mean is so sensitive, why use it in the first place?
We use the mean more than the median because it is additive, in two senses. (I am surprised that in 11 years, no one has really said this!)
If data on a population is broken down into data about men |
1,988 | Interpreting plot.lm() | As stated in the documentation, plot.lm() can return 6 different plots:
[1] a plot of residuals against fitted values, [2] a Scale-Location plot of sqrt(| residuals |) against fitted values, [3] a Normal Q-Q plot, [4] a plot
of Cook's distances versus row labels, [5] a plot of residuals against
leverages, and [6... | Interpreting plot.lm() | As stated in the documentation, plot.lm() can return 6 different plots:
[1] a plot of residuals against fitted values, [2] a Scale-Location plot of sqrt(| residuals |) against fitted values, [3] a | Interpreting plot.lm()
As stated in the documentation, plot.lm() can return 6 different plots:
[1] a plot of residuals against fitted values, [2] a Scale-Location plot of sqrt(| residuals |) against fitted values, [3] a Normal Q-Q plot, [4] a plot
of Cook's distances versus row labels, [5] a plot of residuals agai... | Interpreting plot.lm()
As stated in the documentation, plot.lm() can return 6 different plots:
[1] a plot of residuals against fitted values, [2] a Scale-Location plot of sqrt(| residuals |) against fitted values, [3] a |
1,989 | When is unbalanced data really a problem in Machine Learning? | Not a direct answer, but it's worth noting that in the statistical literature, some of the prejudice against unbalanced data has historical roots.
Many classical models simplify neatly under the assumption of balanced data, especially for methods like ANOVA that are closely related to experimental design—a traditional ... | When is unbalanced data really a problem in Machine Learning? | Not a direct answer, but it's worth noting that in the statistical literature, some of the prejudice against unbalanced data has historical roots.
Many classical models simplify neatly under the assum | When is unbalanced data really a problem in Machine Learning?
Not a direct answer, but it's worth noting that in the statistical literature, some of the prejudice against unbalanced data has historical roots.
Many classical models simplify neatly under the assumption of balanced data, especially for methods like ANOVA ... | When is unbalanced data really a problem in Machine Learning?
Not a direct answer, but it's worth noting that in the statistical literature, some of the prejudice against unbalanced data has historical roots.
Many classical models simplify neatly under the assum |
1,990 | When is unbalanced data really a problem in Machine Learning? | Unbalanced data is only a problem depending on your application. If for example your data indicates that A happens 99.99% of the time and 0.01% of the time B happens and you try to predict a certain result your algorithm will probably always say A. This is of course correct! It is unlikely for your method to get better... | When is unbalanced data really a problem in Machine Learning? | Unbalanced data is only a problem depending on your application. If for example your data indicates that A happens 99.99% of the time and 0.01% of the time B happens and you try to predict a certain r | When is unbalanced data really a problem in Machine Learning?
Unbalanced data is only a problem depending on your application. If for example your data indicates that A happens 99.99% of the time and 0.01% of the time B happens and you try to predict a certain result your algorithm will probably always say A. This is o... | When is unbalanced data really a problem in Machine Learning?
Unbalanced data is only a problem depending on your application. If for example your data indicates that A happens 99.99% of the time and 0.01% of the time B happens and you try to predict a certain r |
1,991 | When is unbalanced data really a problem in Machine Learning? | WLOG you can focus on imbalance in a single factor, rather than a more nuanced concept of "data sparsity", or small cell counts.
In statistical analyses not focused on learning, we are faced with the issue of providing adequate inference while controlling for one or more effects through adjustment, matching, or weighti... | When is unbalanced data really a problem in Machine Learning? | WLOG you can focus on imbalance in a single factor, rather than a more nuanced concept of "data sparsity", or small cell counts.
In statistical analyses not focused on learning, we are faced with the | When is unbalanced data really a problem in Machine Learning?
WLOG you can focus on imbalance in a single factor, rather than a more nuanced concept of "data sparsity", or small cell counts.
In statistical analyses not focused on learning, we are faced with the issue of providing adequate inference while controlling fo... | When is unbalanced data really a problem in Machine Learning?
WLOG you can focus on imbalance in a single factor, rather than a more nuanced concept of "data sparsity", or small cell counts.
In statistical analyses not focused on learning, we are faced with the |
1,992 | When is unbalanced data really a problem in Machine Learning? | I know I'm late to the party, but: the theory behind the data imbalance problem has been beautifully worked out by Sugiyama (2000) and a huge number of highly cited papers following that, under the keyword "covariate shift adaptation". There is also a whole book devoted to this subject by Sugiyama / Kawanabe from 2012,... | When is unbalanced data really a problem in Machine Learning? | I know I'm late to the party, but: the theory behind the data imbalance problem has been beautifully worked out by Sugiyama (2000) and a huge number of highly cited papers following that, under the ke | When is unbalanced data really a problem in Machine Learning?
I know I'm late to the party, but: the theory behind the data imbalance problem has been beautifully worked out by Sugiyama (2000) and a huge number of highly cited papers following that, under the keyword "covariate shift adaptation". There is also a whole ... | When is unbalanced data really a problem in Machine Learning?
I know I'm late to the party, but: the theory behind the data imbalance problem has been beautifully worked out by Sugiyama (2000) and a huge number of highly cited papers following that, under the ke |
1,993 | When is unbalanced data really a problem in Machine Learning? | Let's assume we have two classes:
A, representing 99.99% of the population
B, representing 0.01% of the population
Let's assume we are interested in identifying class B elements, that could be individuals affected by a rare disease or fraudster.
Just by guessing A learners would score high on their loss-functions and... | When is unbalanced data really a problem in Machine Learning? | Let's assume we have two classes:
A, representing 99.99% of the population
B, representing 0.01% of the population
Let's assume we are interested in identifying class B elements, that could be indiv | When is unbalanced data really a problem in Machine Learning?
Let's assume we have two classes:
A, representing 99.99% of the population
B, representing 0.01% of the population
Let's assume we are interested in identifying class B elements, that could be individuals affected by a rare disease or fraudster.
Just by gu... | When is unbalanced data really a problem in Machine Learning?
Let's assume we have two classes:
A, representing 99.99% of the population
B, representing 0.01% of the population
Let's assume we are interested in identifying class B elements, that could be indiv |
1,994 | When is unbalanced data really a problem in Machine Learning? | If you think about it: On a perfectly separable highly imbalanced data set, almost any algorithm will perform without errors.
Hence, it is more a problem of noise in data and less tied to a particular algorithm. And you don't know beforehand which algorithm compensates for one particular type of noise best.
In the end ... | When is unbalanced data really a problem in Machine Learning? | If you think about it: On a perfectly separable highly imbalanced data set, almost any algorithm will perform without errors.
Hence, it is more a problem of noise in data and less tied to a particular | When is unbalanced data really a problem in Machine Learning?
If you think about it: On a perfectly separable highly imbalanced data set, almost any algorithm will perform without errors.
Hence, it is more a problem of noise in data and less tied to a particular algorithm. And you don't know beforehand which algorithm ... | When is unbalanced data really a problem in Machine Learning?
If you think about it: On a perfectly separable highly imbalanced data set, almost any algorithm will perform without errors.
Hence, it is more a problem of noise in data and less tied to a particular |
1,995 | When is unbalanced data really a problem in Machine Learning? | Great answers above, and not sure how much I can add here, but I feel there are three things to consider with imbalanced data, and new trade-offs you'll have to consider when rebalancing. I'd like to frame this in the context of predicting a minority outcome (a common task with imbalanced classes):
By resampling, you ... | When is unbalanced data really a problem in Machine Learning? | Great answers above, and not sure how much I can add here, but I feel there are three things to consider with imbalanced data, and new trade-offs you'll have to consider when rebalancing. I'd like to | When is unbalanced data really a problem in Machine Learning?
Great answers above, and not sure how much I can add here, but I feel there are three things to consider with imbalanced data, and new trade-offs you'll have to consider when rebalancing. I'd like to frame this in the context of predicting a minority outcome... | When is unbalanced data really a problem in Machine Learning?
Great answers above, and not sure how much I can add here, but I feel there are three things to consider with imbalanced data, and new trade-offs you'll have to consider when rebalancing. I'd like to |
1,996 | When is unbalanced data really a problem in Machine Learning? | For me the most important problem with unbalanced data is the baseline estimator. For example, you have two classes with 90% and 10% sample distribution. But what does this mean for a dummy or naive classifier? You can infer this meaning by comparing it with a baseline’s performance. You can always predict the most fr... | When is unbalanced data really a problem in Machine Learning? | For me the most important problem with unbalanced data is the baseline estimator. For example, you have two classes with 90% and 10% sample distribution. But what does this mean for a dummy or naive c | When is unbalanced data really a problem in Machine Learning?
For me the most important problem with unbalanced data is the baseline estimator. For example, you have two classes with 90% and 10% sample distribution. But what does this mean for a dummy or naive classifier? You can infer this meaning by comparing it with... | When is unbalanced data really a problem in Machine Learning?
For me the most important problem with unbalanced data is the baseline estimator. For example, you have two classes with 90% and 10% sample distribution. But what does this mean for a dummy or naive c |
1,997 | What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall? | Personally I remember the difference between precision and recall (a.k.a. sensitivity) by thinking about information retrieval:
Recall is the fraction of the documents that are relevant to the query that are successfully retrieved, hence its name (in English recall = the action of remembering something).
Precision is ... | What is the best way to remember the difference between sensitivity, specificity, precision, accurac | Personally I remember the difference between precision and recall (a.k.a. sensitivity) by thinking about information retrieval:
Recall is the fraction of the documents that are relevant to the query | What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall?
Personally I remember the difference between precision and recall (a.k.a. sensitivity) by thinking about information retrieval:
Recall is the fraction of the documents that are relevant to the query that ... | What is the best way to remember the difference between sensitivity, specificity, precision, accurac
Personally I remember the difference between precision and recall (a.k.a. sensitivity) by thinking about information retrieval:
Recall is the fraction of the documents that are relevant to the query |
1,998 | What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall? | For precision and recall, each is the true positive (TP) as the numerator divided by a different denominator.
Precision: TP / Predicted positive
Recall: TP / Real positive | What is the best way to remember the difference between sensitivity, specificity, precision, accurac | For precision and recall, each is the true positive (TP) as the numerator divided by a different denominator.
Precision: TP / Predicted positive
Recall: TP / Real positive | What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall?
For precision and recall, each is the true positive (TP) as the numerator divided by a different denominator.
Precision: TP / Predicted positive
Recall: TP / Real positive | What is the best way to remember the difference between sensitivity, specificity, precision, accurac
For precision and recall, each is the true positive (TP) as the numerator divided by a different denominator.
Precision: TP / Predicted positive
Recall: TP / Real positive |
1,999 | What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall? | Mnemonics neatly eliminate man’s only nemesis: insufficient cerebral storage.
There is SNOUT SPIN:
A Sensitive test, when Negative rules OUT disease
A Specific test, when Positive, rules IN a disease.
I imagine a pig spinning around in a centrifuge, perhaps in preparation for going into space, to help me remember thi... | What is the best way to remember the difference between sensitivity, specificity, precision, accurac | Mnemonics neatly eliminate man’s only nemesis: insufficient cerebral storage.
There is SNOUT SPIN:
A Sensitive test, when Negative rules OUT disease
A Specific test, when Positive, rules IN a disease | What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall?
Mnemonics neatly eliminate man’s only nemesis: insufficient cerebral storage.
There is SNOUT SPIN:
A Sensitive test, when Negative rules OUT disease
A Specific test, when Positive, rules IN a disease.
I ... | What is the best way to remember the difference between sensitivity, specificity, precision, accurac
Mnemonics neatly eliminate man’s only nemesis: insufficient cerebral storage.
There is SNOUT SPIN:
A Sensitive test, when Negative rules OUT disease
A Specific test, when Positive, rules IN a disease |
2,000 | What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall? | I agree that the terms are very non-intuitive and hard to correspond to their formulas. Here are some diagrams with the mnemonic tricks that I have developed, and now I have them all solidly memorized.
Classification matrix
First, here are the mnemonics summarized in two common variations of the classification matrix (... | What is the best way to remember the difference between sensitivity, specificity, precision, accurac | I agree that the terms are very non-intuitive and hard to correspond to their formulas. Here are some diagrams with the mnemonic tricks that I have developed, and now I have them all solidly memorized | What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall?
I agree that the terms are very non-intuitive and hard to correspond to their formulas. Here are some diagrams with the mnemonic tricks that I have developed, and now I have them all solidly memorized.
Cla... | What is the best way to remember the difference between sensitivity, specificity, precision, accurac
I agree that the terms are very non-intuitive and hard to correspond to their formulas. Here are some diagrams with the mnemonic tricks that I have developed, and now I have them all solidly memorized |
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