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2,501 | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis? | Part 1. Pictures & theory
In this my answer (a second and additional to the other of mine here) I will try to show in pictures that PCA does not restore a covariance any well (whereas it restores - maximizes - variance optimally).
As in a number of my answers on PCA or Factor analysis I will turn to vector representat... | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysi | Part 1. Pictures & theory
In this my answer (a second and additional to the other of mine here) I will try to show in pictures that PCA does not restore a covariance any well (whereas it restores - m | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis?
Part 1. Pictures & theory
In this my answer (a second and additional to the other of mine here) I will try to show in pictures that PCA does not restore a covariance any well (whereas it restores - maximizes - varian... | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysi
Part 1. Pictures & theory
In this my answer (a second and additional to the other of mine here) I will try to show in pictures that PCA does not restore a covariance any well (whereas it restores - m |
2,502 | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis? | (This is really a comment to @ttnphns's second answer)
As far as the different type of reproduction of covariance assuming error by PC and by FA is concerned, I've simply printed out the loadings/components of variance which occur in the two procedures; just for the examples I took 2 variables.
We assume the construct... | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysi | (This is really a comment to @ttnphns's second answer)
As far as the different type of reproduction of covariance assuming error by PC and by FA is concerned, I've simply printed out the loadings/com | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis?
(This is really a comment to @ttnphns's second answer)
As far as the different type of reproduction of covariance assuming error by PC and by FA is concerned, I've simply printed out the loadings/components of varian... | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysi
(This is really a comment to @ttnphns's second answer)
As far as the different type of reproduction of covariance assuming error by PC and by FA is concerned, I've simply printed out the loadings/com |
2,503 | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis? | In my view, the notions of "PCA" and "FA" are on a different dimension from that of notions of "exploratory", "confirmatory" or maybe "inferential". So each of the two mathematical/statistical methods can be applied with one of the three approaches.
For instance, why should it be unsensical to have a hypothese, ... | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysi | In my view, the notions of "PCA" and "FA" are on a different dimension from that of notions of "exploratory", "confirmatory" or maybe "inferential". So each of the two mathematical/statistical meth | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis?
In my view, the notions of "PCA" and "FA" are on a different dimension from that of notions of "exploratory", "confirmatory" or maybe "inferential". So each of the two mathematical/statistical methods can be applie... | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysi
In my view, the notions of "PCA" and "FA" are on a different dimension from that of notions of "exploratory", "confirmatory" or maybe "inferential". So each of the two mathematical/statistical meth |
2,504 | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis? | Just one additional remark for @amoebas's long (and really great) answer on the character of the $\Psi$-estimate.
In your initial statements you have three $\Psi$: for PCA is $ \Psi = 0$, for PPCA is $ \Psi=\sigma ^2 I $ and for FA you left $\Psi$ indeterminate.
But it should be mentioned, that there ... | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysi | Just one additional remark for @amoebas's long (and really great) answer on the character of the $\Psi$-estimate.
In your initial statements you have three $\Psi$: for PCA is $ \Psi = 0$, f | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis?
Just one additional remark for @amoebas's long (and really great) answer on the character of the $\Psi$-estimate.
In your initial statements you have three $\Psi$: for PCA is $ \Psi = 0$, for PPCA is $ \Psi... | Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysi
Just one additional remark for @amoebas's long (and really great) answer on the character of the $\Psi$-estimate.
In your initial statements you have three $\Psi$: for PCA is $ \Psi = 0$, f |
2,505 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | All the answers so far provided are helpful, but they aren't very statistically precise, so I'll take a shot at that. At the same time, I'm going to give a general answer rather than focusing on this election.
The first thing to keep in mind when we're trying to answer questions about real-world events like Clinton win... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | All the answers so far provided are helpful, but they aren't very statistically precise, so I'll take a shot at that. At the same time, I'm going to give a general answer rather than focusing on this | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
All the answers so far provided are helpful, but they aren't very statistically precise, so I'll take a shot at that. At the same time, I'm going to give a general answer rather than focusing on t... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
All the answers so far provided are helpful, but they aren't very statistically precise, so I'll take a shot at that. At the same time, I'm going to give a general answer rather than focusing on this |
2,506 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | When statisticians want to predict a binary outcome (Hillary wins vs Hillary does not win), they imagine that the universe is tossing an imaginary coin - Heads, Hillary wins; tails, she loses. To some statisticians, the coin represents their degree of belief in the outcome; to others, the coin represents what might hap... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | When statisticians want to predict a binary outcome (Hillary wins vs Hillary does not win), they imagine that the universe is tossing an imaginary coin - Heads, Hillary wins; tails, she loses. To some | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
When statisticians want to predict a binary outcome (Hillary wins vs Hillary does not win), they imagine that the universe is tossing an imaginary coin - Heads, Hillary wins; tails, she loses. To ... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
When statisticians want to predict a binary outcome (Hillary wins vs Hillary does not win), they imagine that the universe is tossing an imaginary coin - Heads, Hillary wins; tails, she loses. To some |
2,507 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | When statisticians say this they are not referring to the margin of victory or the share of the vote. They are running a large number of simulations of the election and counting what percentage of the vote each candidate gains. For many robust presidential models they have forecasts for each state. Some are close and i... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | When statisticians say this they are not referring to the margin of victory or the share of the vote. They are running a large number of simulations of the election and counting what percentage of the | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
When statisticians say this they are not referring to the margin of victory or the share of the vote. They are running a large number of simulations of the election and counting what percentage of... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
When statisticians say this they are not referring to the margin of victory or the share of the vote. They are running a large number of simulations of the election and counting what percentage of the |
2,508 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | There's an episode of freakonomics radio that is very relevant to this question (in general, not in the specifics of en election). In it, Stephen Dubner interviews the lead of a project from a United States defense agency to determine the best way to forecast global political events.
It [also] helps a lot to know mor... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | There's an episode of freakonomics radio that is very relevant to this question (in general, not in the specifics of en election). In it, Stephen Dubner interviews the lead of a project from a United | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
There's an episode of freakonomics radio that is very relevant to this question (in general, not in the specifics of en election). In it, Stephen Dubner interviews the lead of a project from a Un... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
There's an episode of freakonomics radio that is very relevant to this question (in general, not in the specifics of en election). In it, Stephen Dubner interviews the lead of a project from a United |
2,509 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | The 2016 election is indeed a one time event. But so is the flip of a coin or the toss of a die.
When someone claims they know a candidate has a 75% chance of winning they are not predicting the outcome. They are claiming they know the shape of the die.
The outcome of the election can't invalidate this. But if the... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | The 2016 election is indeed a one time event. But so is the flip of a coin or the toss of a die.
When someone claims they know a candidate has a 75% chance of winning they are not predicting the outc | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
The 2016 election is indeed a one time event. But so is the flip of a coin or the toss of a die.
When someone claims they know a candidate has a 75% chance of winning they are not predicting the ... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
The 2016 election is indeed a one time event. But so is the flip of a coin or the toss of a die.
When someone claims they know a candidate has a 75% chance of winning they are not predicting the outc |
2,510 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | When someone says that "Hillary has a 75% chance of winning", they mean that if you offered them a bet where one person gets 25 dollars if Hillary wins and the other person gets 75 dollars if Hillary does not win, they would consider that a fair bet and have no particular reason to prefer either side.
These percentages... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | When someone says that "Hillary has a 75% chance of winning", they mean that if you offered them a bet where one person gets 25 dollars if Hillary wins and the other person gets 75 dollars if Hillary | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
When someone says that "Hillary has a 75% chance of winning", they mean that if you offered them a bet where one person gets 25 dollars if Hillary wins and the other person gets 75 dollars if Hill... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
When someone says that "Hillary has a 75% chance of winning", they mean that if you offered them a bet where one person gets 25 dollars if Hillary wins and the other person gets 75 dollars if Hillary |
2,511 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | The key question is how do you assign a probability to a unique event.the answer is that you develop a model by which it is no longer unique. I think an easier example is what is the probability of the president dying in office? You may view the president as a person of a certain age, as a person of a certain age and s... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | The key question is how do you assign a probability to a unique event.the answer is that you develop a model by which it is no longer unique. I think an easier example is what is the probability of th | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
The key question is how do you assign a probability to a unique event.the answer is that you develop a model by which it is no longer unique. I think an easier example is what is the probability o... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
The key question is how do you assign a probability to a unique event.the answer is that you develop a model by which it is no longer unique. I think an easier example is what is the probability of th |
2,512 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | Given the polls show a very tight race, the 75% may or may not be accurate.
You are asking what it means, not how did they calculate this. The implication is that (if we ignore anyone else except Clinton and her one major opponent) that you would need to bet \$3 to get a \$4 return if she wins. Alternately, a \$1 bet ... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | Given the polls show a very tight race, the 75% may or may not be accurate.
You are asking what it means, not how did they calculate this. The implication is that (if we ignore anyone else except Cli | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
Given the polls show a very tight race, the 75% may or may not be accurate.
You are asking what it means, not how did they calculate this. The implication is that (if we ignore anyone else except... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
Given the polls show a very tight race, the 75% may or may not be accurate.
You are asking what it means, not how did they calculate this. The implication is that (if we ignore anyone else except Cli |
2,513 | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"? | If they're doing it right, something happens approximately three-fourths of those times when they say it had a 75% chance of happening. (or more generally, the same idea adapted over all percentage forecasts)
It is possible to ascribe more meaning than that depending on our philosophical opinions and how much we believ... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a | If they're doing it right, something happens approximately three-fourths of those times when they say it had a 75% chance of happening. (or more generally, the same idea adapted over all percentage fo | Probability of a single real-life future event: What does it mean when they say that "Hillary has a 75% chance of winning"?
If they're doing it right, something happens approximately three-fourths of those times when they say it had a 75% chance of happening. (or more generally, the same idea adapted over all percentag... | Probability of a single real-life future event: What does it mean when they say that "Hillary has a
If they're doing it right, something happens approximately three-fourths of those times when they say it had a 75% chance of happening. (or more generally, the same idea adapted over all percentage fo |
2,514 | How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)? | Well, I think it is really difficult to present a visual explanation of Canonical correlation analysis (CCA) vis-a-vis Principal components analysis (PCA) or Linear regression. The latter two are often explained and compared by means of a 2D or 3D data scatterplots, but I doubt if that is possible with CCA. Below I've ... | How to visualize what canonical correlation analysis does (in comparison to what principal component | Well, I think it is really difficult to present a visual explanation of Canonical correlation analysis (CCA) vis-a-vis Principal components analysis (PCA) or Linear regression. The latter two are ofte | How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
Well, I think it is really difficult to present a visual explanation of Canonical correlation analysis (CCA) vis-a-vis Principal components analysis (PCA) or Linear regression. The latter two are often e... | How to visualize what canonical correlation analysis does (in comparison to what principal component
Well, I think it is really difficult to present a visual explanation of Canonical correlation analysis (CCA) vis-a-vis Principal components analysis (PCA) or Linear regression. The latter two are ofte |
2,515 | How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)? | For me it was much helpful to read in the book of S. Mulaik "The Foundations of Factoranalysis" (1972), that there is a method purely of rotations of a matrix of factor loadings to arrive at a canonical correlation, so I could locate it in that ensemble of concepts which I had already understood so far from principal c... | How to visualize what canonical correlation analysis does (in comparison to what principal component | For me it was much helpful to read in the book of S. Mulaik "The Foundations of Factoranalysis" (1972), that there is a method purely of rotations of a matrix of factor loadings to arrive at a canonic | How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
For me it was much helpful to read in the book of S. Mulaik "The Foundations of Factoranalysis" (1972), that there is a method purely of rotations of a matrix of factor loadings to arrive at a canonical ... | How to visualize what canonical correlation analysis does (in comparison to what principal component
For me it was much helpful to read in the book of S. Mulaik "The Foundations of Factoranalysis" (1972), that there is a method purely of rotations of a matrix of factor loadings to arrive at a canonic |
2,516 | How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)? | This answer doesn't provide a visual aid for understanding CCA, however a good geometric interpretation of CCA is presented in Chapter 12 of Anderson-1958 [1]. The gist of it is as follows:
Consider $N$ data points $x_1, x_2, ..., x_N$, all of dimension $p$. Let $X$ be the $p\times N$ matrix containing $x_i$. One way o... | How to visualize what canonical correlation analysis does (in comparison to what principal component | This answer doesn't provide a visual aid for understanding CCA, however a good geometric interpretation of CCA is presented in Chapter 12 of Anderson-1958 [1]. The gist of it is as follows:
Consider $ | How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
This answer doesn't provide a visual aid for understanding CCA, however a good geometric interpretation of CCA is presented in Chapter 12 of Anderson-1958 [1]. The gist of it is as follows:
Consider $N$ ... | How to visualize what canonical correlation analysis does (in comparison to what principal component
This answer doesn't provide a visual aid for understanding CCA, however a good geometric interpretation of CCA is presented in Chapter 12 of Anderson-1958 [1]. The gist of it is as follows:
Consider $ |
2,517 | How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)? | The best way to teach statistics is with data. Multivariate statistical techniques are often made very complicated with matrices which are not intuitive. I would explain CCA using Excel. Create two samples, add new variates (columns basically) and show the calculation. And as far as the matrix construction of CCA is co... | How to visualize what canonical correlation analysis does (in comparison to what principal component | The best way to teach statistics is with data. Multivariate statistical techniques are often made very complicated with matrices which are not intuitive. I would explain CCA using Excel. Create two sa | How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
The best way to teach statistics is with data. Multivariate statistical techniques are often made very complicated with matrices which are not intuitive. I would explain CCA using Excel. Create two sampl... | How to visualize what canonical correlation analysis does (in comparison to what principal component
The best way to teach statistics is with data. Multivariate statistical techniques are often made very complicated with matrices which are not intuitive. I would explain CCA using Excel. Create two sa |
2,518 | What is global max pooling layer and what is its advantage over maxpooling layer? | Global max pooling = ordinary max pooling layer with pool size equals to the size of the input (minus filter size + 1, to be precise). You can see that MaxPooling1D takes a pool_length argument, whereas GlobalMaxPooling1D does not.
For example, if the input of the max pooling layer is $0,1,2,2,5,1,2$, global max poo... | What is global max pooling layer and what is its advantage over maxpooling layer? | Global max pooling = ordinary max pooling layer with pool size equals to the size of the input (minus filter size + 1, to be precise). You can see that MaxPooling1D takes a pool_length argument, whe | What is global max pooling layer and what is its advantage over maxpooling layer?
Global max pooling = ordinary max pooling layer with pool size equals to the size of the input (minus filter size + 1, to be precise). You can see that MaxPooling1D takes a pool_length argument, whereas GlobalMaxPooling1D does not.
For ... | What is global max pooling layer and what is its advantage over maxpooling layer?
Global max pooling = ordinary max pooling layer with pool size equals to the size of the input (minus filter size + 1, to be precise). You can see that MaxPooling1D takes a pool_length argument, whe |
2,519 | What is global max pooling layer and what is its advantage over maxpooling layer? | As described in this paper that proposed global average pooling (GAP):
Conventional convolutional neural networks perform convolution in the lower layers of the network. For classification, the feature maps of the last convolutional layer are vectorized and fed into fully connected layers followed by a softmax logistic... | What is global max pooling layer and what is its advantage over maxpooling layer? | As described in this paper that proposed global average pooling (GAP):
Conventional convolutional neural networks perform convolution in the lower layers of the network. For classification, the featur | What is global max pooling layer and what is its advantage over maxpooling layer?
As described in this paper that proposed global average pooling (GAP):
Conventional convolutional neural networks perform convolution in the lower layers of the network. For classification, the feature maps of the last convolutional layer... | What is global max pooling layer and what is its advantage over maxpooling layer?
As described in this paper that proposed global average pooling (GAP):
Conventional convolutional neural networks perform convolution in the lower layers of the network. For classification, the featur |
2,520 | Help me understand Support Vector Machines | I think you are trying to start from a bad end. What one should know about SVM to use it is just that this algorithm is finding a hyperplane in hyperspace of attributes that separates two classes best, where best means with biggest margin between classes (the knowledge how it is done is your enemy here, because it blur... | Help me understand Support Vector Machines | I think you are trying to start from a bad end. What one should know about SVM to use it is just that this algorithm is finding a hyperplane in hyperspace of attributes that separates two classes best | Help me understand Support Vector Machines
I think you are trying to start from a bad end. What one should know about SVM to use it is just that this algorithm is finding a hyperplane in hyperspace of attributes that separates two classes best, where best means with biggest margin between classes (the knowledge how it ... | Help me understand Support Vector Machines
I think you are trying to start from a bad end. What one should know about SVM to use it is just that this algorithm is finding a hyperplane in hyperspace of attributes that separates two classes best |
2,521 | What's so 'moment' about 'moments' of a probability distribution? | According to the paper "First (?) Occurrence of Common Terms in Mathematical Statistics" by H.A. David, the first use of the word 'moment' in this situation was in a 1893 letter to Nature by Karl Pearson entitled "Asymmetrical Frequency Curves".
Neyman's 1938 Biometrika paper "A Historical Note on Karl Pearson's Deduct... | What's so 'moment' about 'moments' of a probability distribution? | According to the paper "First (?) Occurrence of Common Terms in Mathematical Statistics" by H.A. David, the first use of the word 'moment' in this situation was in a 1893 letter to Nature by Karl Pear | What's so 'moment' about 'moments' of a probability distribution?
According to the paper "First (?) Occurrence of Common Terms in Mathematical Statistics" by H.A. David, the first use of the word 'moment' in this situation was in a 1893 letter to Nature by Karl Pearson entitled "Asymmetrical Frequency Curves".
Neyman's... | What's so 'moment' about 'moments' of a probability distribution?
According to the paper "First (?) Occurrence of Common Terms in Mathematical Statistics" by H.A. David, the first use of the word 'moment' in this situation was in a 1893 letter to Nature by Karl Pear |
2,522 | What's so 'moment' about 'moments' of a probability distribution? | Everybody has its moment on moments. I had mine in Cumulant and moment names beyond variance, skewness and kurtosis, and spent some time reading this gorgious thread.
Oddly, I did not find the "moment mention" in " H. A. David's paper. So I went to
Karl Pearson: The Scientific Life in a Statistical Age, a book by ... | What's so 'moment' about 'moments' of a probability distribution? | Everybody has its moment on moments. I had mine in Cumulant and moment names beyond variance, skewness and kurtosis, and spent some time reading this gorgious thread.
Oddly, I did not find the "mom | What's so 'moment' about 'moments' of a probability distribution?
Everybody has its moment on moments. I had mine in Cumulant and moment names beyond variance, skewness and kurtosis, and spent some time reading this gorgious thread.
Oddly, I did not find the "moment mention" in " H. A. David's paper. So I went to
... | What's so 'moment' about 'moments' of a probability distribution?
Everybody has its moment on moments. I had mine in Cumulant and moment names beyond variance, skewness and kurtosis, and spent some time reading this gorgious thread.
Oddly, I did not find the "mom |
2,523 | What's so 'moment' about 'moments' of a probability distribution? | Question: So what does the word "moment" mean in this case? Why this choice of word? It doesn't sound intuitive to me (or I never heard it that way back in college :) Come to think of it I am equally curious with its usage in "moment of inertia" ;) but let's not focus on that for now.
Answer: Actually, in a historical ... | What's so 'moment' about 'moments' of a probability distribution? | Question: So what does the word "moment" mean in this case? Why this choice of word? It doesn't sound intuitive to me (or I never heard it that way back in college :) Come to think of it I am equally | What's so 'moment' about 'moments' of a probability distribution?
Question: So what does the word "moment" mean in this case? Why this choice of word? It doesn't sound intuitive to me (or I never heard it that way back in college :) Come to think of it I am equally curious with its usage in "moment of inertia" ;) but l... | What's so 'moment' about 'moments' of a probability distribution?
Question: So what does the word "moment" mean in this case? Why this choice of word? It doesn't sound intuitive to me (or I never heard it that way back in college :) Come to think of it I am equally |
2,524 | What's so 'moment' about 'moments' of a probability distribution? | Being overly simplistic, statistical moments are additional descriptors of a curve/distribution. We are familiar with the first two moments and these are generally useful for continuous normal distributions or similar curves. However these first two moments lose their informational value for other distributions. Thus o... | What's so 'moment' about 'moments' of a probability distribution? | Being overly simplistic, statistical moments are additional descriptors of a curve/distribution. We are familiar with the first two moments and these are generally useful for continuous normal distrib | What's so 'moment' about 'moments' of a probability distribution?
Being overly simplistic, statistical moments are additional descriptors of a curve/distribution. We are familiar with the first two moments and these are generally useful for continuous normal distributions or similar curves. However these first two mome... | What's so 'moment' about 'moments' of a probability distribution?
Being overly simplistic, statistical moments are additional descriptors of a curve/distribution. We are familiar with the first two moments and these are generally useful for continuous normal distrib |
2,525 | What is wrong with extrapolation? | A regression model is often used for extrapolation, i.e. predicting the response to an input which lies outside of the range of the values of the predictor variable used to fit the model. The danger associated with extrapolation is illustrated in the following figure.
The regression model is “by construction” an inter... | What is wrong with extrapolation? | A regression model is often used for extrapolation, i.e. predicting the response to an input which lies outside of the range of the values of the predictor variable used to fit the model. The danger a | What is wrong with extrapolation?
A regression model is often used for extrapolation, i.e. predicting the response to an input which lies outside of the range of the values of the predictor variable used to fit the model. The danger associated with extrapolation is illustrated in the following figure.
The regression m... | What is wrong with extrapolation?
A regression model is often used for extrapolation, i.e. predicting the response to an input which lies outside of the range of the values of the predictor variable used to fit the model. The danger a |
2,526 | What is wrong with extrapolation? | This xkcd comic explains it all.
Using the data points Cueball (the man with the stick) has, he has extrapolated that the woman will have "four dozen" husbands by late next month, and used this extrapolation to lead to the conclusion of buying the wedding cake in bulk.
Edit 3: For those of you who say "he doesn't have... | What is wrong with extrapolation? | This xkcd comic explains it all.
Using the data points Cueball (the man with the stick) has, he has extrapolated that the woman will have "four dozen" husbands by late next month, and used this extra | What is wrong with extrapolation?
This xkcd comic explains it all.
Using the data points Cueball (the man with the stick) has, he has extrapolated that the woman will have "four dozen" husbands by late next month, and used this extrapolation to lead to the conclusion of buying the wedding cake in bulk.
Edit 3: For tho... | What is wrong with extrapolation?
This xkcd comic explains it all.
Using the data points Cueball (the man with the stick) has, he has extrapolated that the woman will have "four dozen" husbands by late next month, and used this extra |
2,527 | What is wrong with extrapolation? | "Prediction is very difficult, especially if it's about the future". The quote is attributed to many people in some form. I restrict in the following "extrapolation" to "prediction outside the known range", and in a one-dimensional setting, extrapolation from a known past to an unknown future.
So what is wrong with ex... | What is wrong with extrapolation? | "Prediction is very difficult, especially if it's about the future". The quote is attributed to many people in some form. I restrict in the following "extrapolation" to "prediction outside the known | What is wrong with extrapolation?
"Prediction is very difficult, especially if it's about the future". The quote is attributed to many people in some form. I restrict in the following "extrapolation" to "prediction outside the known range", and in a one-dimensional setting, extrapolation from a known past to an unknow... | What is wrong with extrapolation?
"Prediction is very difficult, especially if it's about the future". The quote is attributed to many people in some form. I restrict in the following "extrapolation" to "prediction outside the known |
2,528 | What is wrong with extrapolation? | Although the fit of a model might be "good", extrapolation beyond the range of the data must be treated skeptically. The reason is that in many cases extrapolation (unfortunately and unavoidably) relies on untestable assumptions
about the behaviour of the data beyond their observed support.
When extrapolating one must ... | What is wrong with extrapolation? | Although the fit of a model might be "good", extrapolation beyond the range of the data must be treated skeptically. The reason is that in many cases extrapolation (unfortunately and unavoidably) reli | What is wrong with extrapolation?
Although the fit of a model might be "good", extrapolation beyond the range of the data must be treated skeptically. The reason is that in many cases extrapolation (unfortunately and unavoidably) relies on untestable assumptions
about the behaviour of the data beyond their observed sup... | What is wrong with extrapolation?
Although the fit of a model might be "good", extrapolation beyond the range of the data must be treated skeptically. The reason is that in many cases extrapolation (unfortunately and unavoidably) reli |
2,529 | What is wrong with extrapolation? | Contrary to other answers, I'd say that there is nothing wrong with extrapolation as far as it is not used in mindless way. First, notice that extrapolation is:
the process of estimating, beyond the
original observation range, the value of a variable on the basis of
its relationship with another variable.
...so it's ... | What is wrong with extrapolation? | Contrary to other answers, I'd say that there is nothing wrong with extrapolation as far as it is not used in mindless way. First, notice that extrapolation is:
the process of estimating, beyond the
| What is wrong with extrapolation?
Contrary to other answers, I'd say that there is nothing wrong with extrapolation as far as it is not used in mindless way. First, notice that extrapolation is:
the process of estimating, beyond the
original observation range, the value of a variable on the basis of
its relationship w... | What is wrong with extrapolation?
Contrary to other answers, I'd say that there is nothing wrong with extrapolation as far as it is not used in mindless way. First, notice that extrapolation is:
the process of estimating, beyond the
|
2,530 | What is wrong with extrapolation? | I quite like the example by Nassim Taleb (which was an adaptation of an earlier example by Bertrand Russell):
Consider a turkey that is fed every day. Every single feeding will firm up the bird's belief that it is the general rule of life to be fed every day by friendly members of the human race "looking out for its b... | What is wrong with extrapolation? | I quite like the example by Nassim Taleb (which was an adaptation of an earlier example by Bertrand Russell):
Consider a turkey that is fed every day. Every single feeding will firm up the bird's bel | What is wrong with extrapolation?
I quite like the example by Nassim Taleb (which was an adaptation of an earlier example by Bertrand Russell):
Consider a turkey that is fed every day. Every single feeding will firm up the bird's belief that it is the general rule of life to be fed every day by friendly members of the... | What is wrong with extrapolation?
I quite like the example by Nassim Taleb (which was an adaptation of an earlier example by Bertrand Russell):
Consider a turkey that is fed every day. Every single feeding will firm up the bird's bel |
2,531 | What is wrong with extrapolation? | Ponder the following story, if you will.
I also remember sitting in a Statistics course, and the professor told us extrapolation was a bad idea. Then during the next class he told us it was a bad idea again; in fact, he said it twice.
I was sick for the rest of the semester, but I was certain I couldn't have missed a l... | What is wrong with extrapolation? | Ponder the following story, if you will.
I also remember sitting in a Statistics course, and the professor told us extrapolation was a bad idea. Then during the next class he told us it was a bad idea | What is wrong with extrapolation?
Ponder the following story, if you will.
I also remember sitting in a Statistics course, and the professor told us extrapolation was a bad idea. Then during the next class he told us it was a bad idea again; in fact, he said it twice.
I was sick for the rest of the semester, but I was ... | What is wrong with extrapolation?
Ponder the following story, if you will.
I also remember sitting in a Statistics course, and the professor told us extrapolation was a bad idea. Then during the next class he told us it was a bad idea |
2,532 | What is wrong with extrapolation? | The question is not just statistical, it's also epistemological. Extrapolation is one of the ways we learn about the nature, it's a form of induction.
Let's say we have data for electrical conductivity of a material in a range of temperatures from 0 to 20 Celsius, what can we say about the conductivity at 40 degree Ce... | What is wrong with extrapolation? | The question is not just statistical, it's also epistemological. Extrapolation is one of the ways we learn about the nature, it's a form of induction.
Let's say we have data for electrical conductivi | What is wrong with extrapolation?
The question is not just statistical, it's also epistemological. Extrapolation is one of the ways we learn about the nature, it's a form of induction.
Let's say we have data for electrical conductivity of a material in a range of temperatures from 0 to 20 Celsius, what can we say abou... | What is wrong with extrapolation?
The question is not just statistical, it's also epistemological. Extrapolation is one of the ways we learn about the nature, it's a form of induction.
Let's say we have data for electrical conductivi |
2,533 | What is wrong with extrapolation? | Extrapolation itself isn't necessarily evil, but it is a process which lends itself to conclusions which are more unreasonable than you arrive at with interpolation.
Extrapolation is often done to explore values quite far from the sampled region. If I'm sampling 100 values from 0-10, and then extrapolate out just a l... | What is wrong with extrapolation? | Extrapolation itself isn't necessarily evil, but it is a process which lends itself to conclusions which are more unreasonable than you arrive at with interpolation.
Extrapolation is often done to ex | What is wrong with extrapolation?
Extrapolation itself isn't necessarily evil, but it is a process which lends itself to conclusions which are more unreasonable than you arrive at with interpolation.
Extrapolation is often done to explore values quite far from the sampled region. If I'm sampling 100 values from 0-10,... | What is wrong with extrapolation?
Extrapolation itself isn't necessarily evil, but it is a process which lends itself to conclusions which are more unreasonable than you arrive at with interpolation.
Extrapolation is often done to ex |
2,534 | What is wrong with extrapolation? | Lots of good answers here, I just want to try and synthesize what I see as the core of the issue: it is dangerous to extrapolate beyond that data generating process that gave rise to the estimation sample. This is sometimes called a 'structural change'.
Forecasting comes with assumptions, the main one being that the ... | What is wrong with extrapolation? | Lots of good answers here, I just want to try and synthesize what I see as the core of the issue: it is dangerous to extrapolate beyond that data generating process that gave rise to the estimation sa | What is wrong with extrapolation?
Lots of good answers here, I just want to try and synthesize what I see as the core of the issue: it is dangerous to extrapolate beyond that data generating process that gave rise to the estimation sample. This is sometimes called a 'structural change'.
Forecasting comes with assumpt... | What is wrong with extrapolation?
Lots of good answers here, I just want to try and synthesize what I see as the core of the issue: it is dangerous to extrapolate beyond that data generating process that gave rise to the estimation sa |
2,535 | Examples for teaching: Correlation does not mean causation | It might be useful to explain that "causes" is an asymmetric relation (X causes Y is different from Y causes X), whereas "is correlated with" is a symmetric relation.
For instance, homeless population and crime rate might be correlated, in that both tend to be high or low in the same locations. It is equally valid to ... | Examples for teaching: Correlation does not mean causation | It might be useful to explain that "causes" is an asymmetric relation (X causes Y is different from Y causes X), whereas "is correlated with" is a symmetric relation.
For instance, homeless population | Examples for teaching: Correlation does not mean causation
It might be useful to explain that "causes" is an asymmetric relation (X causes Y is different from Y causes X), whereas "is correlated with" is a symmetric relation.
For instance, homeless population and crime rate might be correlated, in that both tend to be ... | Examples for teaching: Correlation does not mean causation
It might be useful to explain that "causes" is an asymmetric relation (X causes Y is different from Y causes X), whereas "is correlated with" is a symmetric relation.
For instance, homeless population |
2,536 | Examples for teaching: Correlation does not mean causation | My favorites:
1) The more firemen are sent to a fire, the more damage is done.
2) Children who get tutored get worse grades than children who do not get tutored
and (this is my top one)
3) In the early elementary school years, astrological sign is correlated with IQ, but this correlation weakens with age and disappear... | Examples for teaching: Correlation does not mean causation | My favorites:
1) The more firemen are sent to a fire, the more damage is done.
2) Children who get tutored get worse grades than children who do not get tutored
and (this is my top one)
3) In the ear | Examples for teaching: Correlation does not mean causation
My favorites:
1) The more firemen are sent to a fire, the more damage is done.
2) Children who get tutored get worse grades than children who do not get tutored
and (this is my top one)
3) In the early elementary school years, astrological sign is correlated w... | Examples for teaching: Correlation does not mean causation
My favorites:
1) The more firemen are sent to a fire, the more damage is done.
2) Children who get tutored get worse grades than children who do not get tutored
and (this is my top one)
3) In the ear |
2,537 | Examples for teaching: Correlation does not mean causation | I've always liked this one:
source: http://pubs.acs.org/doi/abs/10.1021/ci700332k | Examples for teaching: Correlation does not mean causation | I've always liked this one:
source: http://pubs.acs.org/doi/abs/10.1021/ci700332k | Examples for teaching: Correlation does not mean causation
I've always liked this one:
source: http://pubs.acs.org/doi/abs/10.1021/ci700332k | Examples for teaching: Correlation does not mean causation
I've always liked this one:
source: http://pubs.acs.org/doi/abs/10.1021/ci700332k |
2,538 | Examples for teaching: Correlation does not mean causation | Sometimes correlation is enough. For example, in car insurance, male drivers are correlated with more accidents, so insurance companies charge them more. There is no way you could actually test this for causation. You cannot change the genders of the drivers experimentally. Google has made hundreds of billions of dolla... | Examples for teaching: Correlation does not mean causation | Sometimes correlation is enough. For example, in car insurance, male drivers are correlated with more accidents, so insurance companies charge them more. There is no way you could actually test this f | Examples for teaching: Correlation does not mean causation
Sometimes correlation is enough. For example, in car insurance, male drivers are correlated with more accidents, so insurance companies charge them more. There is no way you could actually test this for causation. You cannot change the genders of the drivers ex... | Examples for teaching: Correlation does not mean causation
Sometimes correlation is enough. For example, in car insurance, male drivers are correlated with more accidents, so insurance companies charge them more. There is no way you could actually test this f |
2,539 | Examples for teaching: Correlation does not mean causation | The number of Nobel prizes won by a country (adjusting for population) correlates well with per capita chocolate consumption. (New England Journal of Medicine) | Examples for teaching: Correlation does not mean causation | The number of Nobel prizes won by a country (adjusting for population) correlates well with per capita chocolate consumption. (New England Journal of Medicine) | Examples for teaching: Correlation does not mean causation
The number of Nobel prizes won by a country (adjusting for population) correlates well with per capita chocolate consumption. (New England Journal of Medicine) | Examples for teaching: Correlation does not mean causation
The number of Nobel prizes won by a country (adjusting for population) correlates well with per capita chocolate consumption. (New England Journal of Medicine) |
2,540 | Examples for teaching: Correlation does not mean causation | I have a few examples I like to use.
When investigating the cause of crime in New York City in the 80s, when they were trying to clean up the city, an academic found a strong correlation between the amount of serious crime committed and the amount of ice cream sold by street vendors! (Which is the cause and which is ... | Examples for teaching: Correlation does not mean causation | I have a few examples I like to use.
When investigating the cause of crime in New York City in the 80s, when they were trying to clean up the city, an academic found a strong correlation between the | Examples for teaching: Correlation does not mean causation
I have a few examples I like to use.
When investigating the cause of crime in New York City in the 80s, when they were trying to clean up the city, an academic found a strong correlation between the amount of serious crime committed and the amount of ice crea... | Examples for teaching: Correlation does not mean causation
I have a few examples I like to use.
When investigating the cause of crime in New York City in the 80s, when they were trying to clean up the city, an academic found a strong correlation between the |
2,541 | Examples for teaching: Correlation does not mean causation | Although it's more of an illustration of the problem of multiple comparisons, it is also a good example of misattributed causation:
Rugby (the religion of Wales) and its influence on the Catholic church: should Pope Benedict XVI be worried?
"every time Wales win the rugby grand slam, a Pope dies, except for 1978 when ... | Examples for teaching: Correlation does not mean causation | Although it's more of an illustration of the problem of multiple comparisons, it is also a good example of misattributed causation:
Rugby (the religion of Wales) and its influence on the Catholic chur | Examples for teaching: Correlation does not mean causation
Although it's more of an illustration of the problem of multiple comparisons, it is also a good example of misattributed causation:
Rugby (the religion of Wales) and its influence on the Catholic church: should Pope Benedict XVI be worried?
"every time Wales w... | Examples for teaching: Correlation does not mean causation
Although it's more of an illustration of the problem of multiple comparisons, it is also a good example of misattributed causation:
Rugby (the religion of Wales) and its influence on the Catholic chur |
2,542 | Examples for teaching: Correlation does not mean causation | There's two aspects to this post hoc ergo propter hoc problem that I like to cover: (i) reverse causality and (ii) endogeneity
An example of "possible" reverse causality:
Social drinking and earnings - drinkers earn more money according to Bethany L. Peters & Edward Stringham (2006. "No Booze? You May Lose: Why Drinke... | Examples for teaching: Correlation does not mean causation | There's two aspects to this post hoc ergo propter hoc problem that I like to cover: (i) reverse causality and (ii) endogeneity
An example of "possible" reverse causality:
Social drinking and earnings | Examples for teaching: Correlation does not mean causation
There's two aspects to this post hoc ergo propter hoc problem that I like to cover: (i) reverse causality and (ii) endogeneity
An example of "possible" reverse causality:
Social drinking and earnings - drinkers earn more money according to Bethany L. Peters & ... | Examples for teaching: Correlation does not mean causation
There's two aspects to this post hoc ergo propter hoc problem that I like to cover: (i) reverse causality and (ii) endogeneity
An example of "possible" reverse causality:
Social drinking and earnings |
2,543 | Examples for teaching: Correlation does not mean causation | The best one I've been taught has been the number of drownings and sales of ice creams may be highly correlated but that doesnt imply one causes the other. Drownings and sales of ice cream are obviously higher in the summer months when the weather is good. Third variable aka good weather causes them. | Examples for teaching: Correlation does not mean causation | The best one I've been taught has been the number of drownings and sales of ice creams may be highly correlated but that doesnt imply one causes the other. Drownings and sales of ice cream are obvious | Examples for teaching: Correlation does not mean causation
The best one I've been taught has been the number of drownings and sales of ice creams may be highly correlated but that doesnt imply one causes the other. Drownings and sales of ice cream are obviously higher in the summer months when the weather is good. Thir... | Examples for teaching: Correlation does not mean causation
The best one I've been taught has been the number of drownings and sales of ice creams may be highly correlated but that doesnt imply one causes the other. Drownings and sales of ice cream are obvious |
2,544 | Examples for teaching: Correlation does not mean causation | As a generalization of 'pirates cause global warming': Pick any two quantities which are (monotonically) increasing or decreasing with time and you should see some correlation. | Examples for teaching: Correlation does not mean causation | As a generalization of 'pirates cause global warming': Pick any two quantities which are (monotonically) increasing or decreasing with time and you should see some correlation. | Examples for teaching: Correlation does not mean causation
As a generalization of 'pirates cause global warming': Pick any two quantities which are (monotonically) increasing or decreasing with time and you should see some correlation. | Examples for teaching: Correlation does not mean causation
As a generalization of 'pirates cause global warming': Pick any two quantities which are (monotonically) increasing or decreasing with time and you should see some correlation. |
2,545 | Examples for teaching: Correlation does not mean causation | I work with students in teaching correlation vs causation in my Algebra One classes. We examine a lot of possible examples. I found the article Bundled-Up Babies and Dangerous Ice Cream: Correlation Puzzlers from the February 2013 Mathematics Teacher to be useful. I like the idea of talking about "lurking variables". ... | Examples for teaching: Correlation does not mean causation | I work with students in teaching correlation vs causation in my Algebra One classes. We examine a lot of possible examples. I found the article Bundled-Up Babies and Dangerous Ice Cream: Correlation P | Examples for teaching: Correlation does not mean causation
I work with students in teaching correlation vs causation in my Algebra One classes. We examine a lot of possible examples. I found the article Bundled-Up Babies and Dangerous Ice Cream: Correlation Puzzlers from the February 2013 Mathematics Teacher to be usef... | Examples for teaching: Correlation does not mean causation
I work with students in teaching correlation vs causation in my Algebra One classes. We examine a lot of possible examples. I found the article Bundled-Up Babies and Dangerous Ice Cream: Correlation P |
2,546 | Examples for teaching: Correlation does not mean causation | You can spend a few minutes on Google Correlate, and come up with all kinds of spurious correlations. | Examples for teaching: Correlation does not mean causation | You can spend a few minutes on Google Correlate, and come up with all kinds of spurious correlations. | Examples for teaching: Correlation does not mean causation
You can spend a few minutes on Google Correlate, and come up with all kinds of spurious correlations. | Examples for teaching: Correlation does not mean causation
You can spend a few minutes on Google Correlate, and come up with all kinds of spurious correlations. |
2,547 | Examples for teaching: Correlation does not mean causation | The standard citation pointing out the correlation between the number of newborn babies and breeding-pairs of storks in West Germany is A new parameter for sex education, Nature 332, 495 (07 April 1988); doi:10.1038/332495a0 | Examples for teaching: Correlation does not mean causation | The standard citation pointing out the correlation between the number of newborn babies and breeding-pairs of storks in West Germany is A new parameter for sex education, Nature 332, 495 (07 April 198 | Examples for teaching: Correlation does not mean causation
The standard citation pointing out the correlation between the number of newborn babies and breeding-pairs of storks in West Germany is A new parameter for sex education, Nature 332, 495 (07 April 1988); doi:10.1038/332495a0 | Examples for teaching: Correlation does not mean causation
The standard citation pointing out the correlation between the number of newborn babies and breeding-pairs of storks in West Germany is A new parameter for sex education, Nature 332, 495 (07 April 198 |
2,548 | Examples for teaching: Correlation does not mean causation | A correlation on its own can never establish a causal link. David Hume (1771-1776) argued quite effectively that we can not obtain certain knowlege of cauasality by purely empirical means. Kant attempted to address this, the Wikipedia page for Kant seems to sum it up quite nicely:
Kant believed himself to be creating... | Examples for teaching: Correlation does not mean causation | A correlation on its own can never establish a causal link. David Hume (1771-1776) argued quite effectively that we can not obtain certain knowlege of cauasality by purely empirical means. Kant atte | Examples for teaching: Correlation does not mean causation
A correlation on its own can never establish a causal link. David Hume (1771-1776) argued quite effectively that we can not obtain certain knowlege of cauasality by purely empirical means. Kant attempted to address this, the Wikipedia page for Kant seems to s... | Examples for teaching: Correlation does not mean causation
A correlation on its own can never establish a causal link. David Hume (1771-1776) argued quite effectively that we can not obtain certain knowlege of cauasality by purely empirical means. Kant atte |
2,549 | Examples for teaching: Correlation does not mean causation | I read (a long time ago) of an interesting example about a decline in birth rates (or fertility rates if you prefer that measure) especially in the US, starting in the early 1960's, as nuclear weapons testing was at an all-time high (in 1961 the biggest nuclear bomb ever detonated was tested in the USSR). Rates contin... | Examples for teaching: Correlation does not mean causation | I read (a long time ago) of an interesting example about a decline in birth rates (or fertility rates if you prefer that measure) especially in the US, starting in the early 1960's, as nuclear weapon | Examples for teaching: Correlation does not mean causation
I read (a long time ago) of an interesting example about a decline in birth rates (or fertility rates if you prefer that measure) especially in the US, starting in the early 1960's, as nuclear weapons testing was at an all-time high (in 1961 the biggest nuclea... | Examples for teaching: Correlation does not mean causation
I read (a long time ago) of an interesting example about a decline in birth rates (or fertility rates if you prefer that measure) especially in the US, starting in the early 1960's, as nuclear weapon |
2,550 | Examples for teaching: Correlation does not mean causation | when $x_t$; $y_t$ are stationary time series, then correlation between $y_t$ and $x_{t-1}$ implies causation of $y_t$ by $x_{t-1}$. For some reason it's not mentioned here. | Examples for teaching: Correlation does not mean causation | when $x_t$; $y_t$ are stationary time series, then correlation between $y_t$ and $x_{t-1}$ implies causation of $y_t$ by $x_{t-1}$. For some reason it's not mentioned here. | Examples for teaching: Correlation does not mean causation
when $x_t$; $y_t$ are stationary time series, then correlation between $y_t$ and $x_{t-1}$ implies causation of $y_t$ by $x_{t-1}$. For some reason it's not mentioned here. | Examples for teaching: Correlation does not mean causation
when $x_t$; $y_t$ are stationary time series, then correlation between $y_t$ and $x_{t-1}$ implies causation of $y_t$ by $x_{t-1}$. For some reason it's not mentioned here. |
2,551 | Examples for teaching: Correlation does not mean causation | Sperm count in males in Slovene villages and the number of bears (also in Slovenia) show a negative correlation. Some people find this very worrying. I'll try and get the study that did this. | Examples for teaching: Correlation does not mean causation | Sperm count in males in Slovene villages and the number of bears (also in Slovenia) show a negative correlation. Some people find this very worrying. I'll try and get the study that did this. | Examples for teaching: Correlation does not mean causation
Sperm count in males in Slovene villages and the number of bears (also in Slovenia) show a negative correlation. Some people find this very worrying. I'll try and get the study that did this. | Examples for teaching: Correlation does not mean causation
Sperm count in males in Slovene villages and the number of bears (also in Slovenia) show a negative correlation. Some people find this very worrying. I'll try and get the study that did this. |
2,552 | Examples for teaching: Correlation does not mean causation | I've recently been to a conference and one of the speakers gave this very interesting example (although the point was to illustrate something else):
Americans and English eat a lot of fat food. There is a high rate of cardiovascular diseases in US and UK.
French eat a lot of fat food, but they have a low(er) rate of c... | Examples for teaching: Correlation does not mean causation | I've recently been to a conference and one of the speakers gave this very interesting example (although the point was to illustrate something else):
Americans and English eat a lot of fat food. There | Examples for teaching: Correlation does not mean causation
I've recently been to a conference and one of the speakers gave this very interesting example (although the point was to illustrate something else):
Americans and English eat a lot of fat food. There is a high rate of cardiovascular diseases in US and UK.
Fren... | Examples for teaching: Correlation does not mean causation
I've recently been to a conference and one of the speakers gave this very interesting example (although the point was to illustrate something else):
Americans and English eat a lot of fat food. There |
2,553 | Examples for teaching: Correlation does not mean causation | This cartoon rom XKCD is also posted elsewhere at CrossValidated. | Examples for teaching: Correlation does not mean causation | This cartoon rom XKCD is also posted elsewhere at CrossValidated. | Examples for teaching: Correlation does not mean causation
This cartoon rom XKCD is also posted elsewhere at CrossValidated. | Examples for teaching: Correlation does not mean causation
This cartoon rom XKCD is also posted elsewhere at CrossValidated. |
2,554 | Examples for teaching: Correlation does not mean causation | Another example of correlation I've used is the large increase in the number of people eating organic food and the increase in the number of children diagnosed with autism in the U.S. There's a parody graph on the web - | Examples for teaching: Correlation does not mean causation | Another example of correlation I've used is the large increase in the number of people eating organic food and the increase in the number of children diagnosed with autism in the U.S. There's a parody | Examples for teaching: Correlation does not mean causation
Another example of correlation I've used is the large increase in the number of people eating organic food and the increase in the number of children diagnosed with autism in the U.S. There's a parody graph on the web - | Examples for teaching: Correlation does not mean causation
Another example of correlation I've used is the large increase in the number of people eating organic food and the increase in the number of children diagnosed with autism in the U.S. There's a parody |
2,555 | Examples for teaching: Correlation does not mean causation | http://tylervigen.com/
This shows a ton of correlations that obviously have nothing to do with causation - Or do you have any good idea what's the causation to the correlation of
Age of Miss America
correlates with
Murders by steam, hot vapours and hot objects
?? | Examples for teaching: Correlation does not mean causation | http://tylervigen.com/
This shows a ton of correlations that obviously have nothing to do with causation - Or do you have any good idea what's the causation to the correlation of
Age of Miss America
c | Examples for teaching: Correlation does not mean causation
http://tylervigen.com/
This shows a ton of correlations that obviously have nothing to do with causation - Or do you have any good idea what's the causation to the correlation of
Age of Miss America
correlates with
Murders by steam, hot vapours and hot objects
... | Examples for teaching: Correlation does not mean causation
http://tylervigen.com/
This shows a ton of correlations that obviously have nothing to do with causation - Or do you have any good idea what's the causation to the correlation of
Age of Miss America
c |
2,556 | Examples for teaching: Correlation does not mean causation | Teaching "Correlation does not mean causation" doesn't really help anyone because at the end of the day all deductive arguments are based in part on correlation.
Human are very bad at learning not to do something.
The goal should rather be constructive: Always think about alternatives to your starting assumptions that... | Examples for teaching: Correlation does not mean causation | Teaching "Correlation does not mean causation" doesn't really help anyone because at the end of the day all deductive arguments are based in part on correlation.
Human are very bad at learning not to | Examples for teaching: Correlation does not mean causation
Teaching "Correlation does not mean causation" doesn't really help anyone because at the end of the day all deductive arguments are based in part on correlation.
Human are very bad at learning not to do something.
The goal should rather be constructive: Always... | Examples for teaching: Correlation does not mean causation
Teaching "Correlation does not mean causation" doesn't really help anyone because at the end of the day all deductive arguments are based in part on correlation.
Human are very bad at learning not to |
2,557 | Examples for teaching: Correlation does not mean causation | Well my Prof. used these in Introductory probability class:
1) Shoe size are correlated with reading ability
2) Shark attack is correlated with sale of ice cream. | Examples for teaching: Correlation does not mean causation | Well my Prof. used these in Introductory probability class:
1) Shoe size are correlated with reading ability
2) Shark attack is correlated with sale of ice cream. | Examples for teaching: Correlation does not mean causation
Well my Prof. used these in Introductory probability class:
1) Shoe size are correlated with reading ability
2) Shark attack is correlated with sale of ice cream. | Examples for teaching: Correlation does not mean causation
Well my Prof. used these in Introductory probability class:
1) Shoe size are correlated with reading ability
2) Shark attack is correlated with sale of ice cream. |
2,558 | Examples for teaching: Correlation does not mean causation | The more fire engines sent to a fire, the bigger the damage. | Examples for teaching: Correlation does not mean causation | The more fire engines sent to a fire, the bigger the damage. | Examples for teaching: Correlation does not mean causation
The more fire engines sent to a fire, the bigger the damage. | Examples for teaching: Correlation does not mean causation
The more fire engines sent to a fire, the bigger the damage. |
2,559 | Examples for teaching: Correlation does not mean causation | I think a better paradigm might be causation requires correlation associated with a credible and preferably proven mechanism. I think the word imply should be used very sparingly in this context, as it has several meanings including that of suggestion. | Examples for teaching: Correlation does not mean causation | I think a better paradigm might be causation requires correlation associated with a credible and preferably proven mechanism. I think the word imply should be used very sparingly in this context, as | Examples for teaching: Correlation does not mean causation
I think a better paradigm might be causation requires correlation associated with a credible and preferably proven mechanism. I think the word imply should be used very sparingly in this context, as it has several meanings including that of suggestion. | Examples for teaching: Correlation does not mean causation
I think a better paradigm might be causation requires correlation associated with a credible and preferably proven mechanism. I think the word imply should be used very sparingly in this context, as |
2,560 | Examples for teaching: Correlation does not mean causation | The storks example is on page 8 of the first edition (1978) of Box, Hunter & Hunter's book entitled "Statistics for Experimenters..." (Wiley). I don't know whether it's in the 2nd edition. They identify the city as Oldenburg and the time period as 1930-1936.
They reference Ornithologische Monatsberichte, 44, No 2, ... | Examples for teaching: Correlation does not mean causation | The storks example is on page 8 of the first edition (1978) of Box, Hunter & Hunter's book entitled "Statistics for Experimenters..." (Wiley). I don't know whether it's in the 2nd edition. They iden | Examples for teaching: Correlation does not mean causation
The storks example is on page 8 of the first edition (1978) of Box, Hunter & Hunter's book entitled "Statistics for Experimenters..." (Wiley). I don't know whether it's in the 2nd edition. They identify the city as Oldenburg and the time period as 1930-1936. ... | Examples for teaching: Correlation does not mean causation
The storks example is on page 8 of the first edition (1978) of Box, Hunter & Hunter's book entitled "Statistics for Experimenters..." (Wiley). I don't know whether it's in the 2nd edition. They iden |
2,561 | Examples for teaching: Correlation does not mean causation | I saw a funny one in an article.
Butter production in Bangladesh has one of the highest correlation with the S&P 500 over a ten year period. | Examples for teaching: Correlation does not mean causation | I saw a funny one in an article.
Butter production in Bangladesh has one of the highest correlation with the S&P 500 over a ten year period. | Examples for teaching: Correlation does not mean causation
I saw a funny one in an article.
Butter production in Bangladesh has one of the highest correlation with the S&P 500 over a ten year period. | Examples for teaching: Correlation does not mean causation
I saw a funny one in an article.
Butter production in Bangladesh has one of the highest correlation with the S&P 500 over a ten year period. |
2,562 | Examples for teaching: Correlation does not mean causation | Here is a perfect one. And unfortunately, it can be used as a great teaching point because neither the Washington Post's staff nor the Centers for Disease Control and Prevention demonstrate any inkling of knowledge that the article should be a satire piece in The Onion.
https://www.washingtonpost.com/health/trumps-pr... | Examples for teaching: Correlation does not mean causation | Here is a perfect one. And unfortunately, it can be used as a great teaching point because neither the Washington Post's staff nor the Centers for Disease Control and Prevention demonstrate any inkli | Examples for teaching: Correlation does not mean causation
Here is a perfect one. And unfortunately, it can be used as a great teaching point because neither the Washington Post's staff nor the Centers for Disease Control and Prevention demonstrate any inkling of knowledge that the article should be a satire piece in ... | Examples for teaching: Correlation does not mean causation
Here is a perfect one. And unfortunately, it can be used as a great teaching point because neither the Washington Post's staff nor the Centers for Disease Control and Prevention demonstrate any inkli |
2,563 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | There are some terminological differences where the same thing is called different names in different disciplines:
Longitudinal data in biostatistics are repeated observations of the same individuals = panel data in econometrics.
The model for a binary dependent variable in which the probability of 1 is modeled as $1/... | What are the major philosophical, methodological, and terminological differences between econometric | There are some terminological differences where the same thing is called different names in different disciplines:
Longitudinal data in biostatistics are repeated observations of the same individuals | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
There are some terminological differences where the same thing is called different names in different disciplines:
Longitudinal data in biostatistics are repeated observations of the same... | What are the major philosophical, methodological, and terminological differences between econometric
There are some terminological differences where the same thing is called different names in different disciplines:
Longitudinal data in biostatistics are repeated observations of the same individuals |
2,564 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | It is best to explain in terms of linear regression, since it is the main tool of econometrics. In linear regression we have a model:
$$Y=X\beta+\varepsilon$$
The main difference between other statistical fields and econometrics is that $X$ is treated as fixed in other fields and is treated as random variable in econom... | What are the major philosophical, methodological, and terminological differences between econometric | It is best to explain in terms of linear regression, since it is the main tool of econometrics. In linear regression we have a model:
$$Y=X\beta+\varepsilon$$
The main difference between other statist | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
It is best to explain in terms of linear regression, since it is the main tool of econometrics. In linear regression we have a model:
$$Y=X\beta+\varepsilon$$
The main difference between o... | What are the major philosophical, methodological, and terminological differences between econometric
It is best to explain in terms of linear regression, since it is the main tool of econometrics. In linear regression we have a model:
$$Y=X\beta+\varepsilon$$
The main difference between other statist |
2,565 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | Of course, any broad statements are bound to be overly broad. But my experience has been that econometrics is concerned about causal relationships and statistics has become more interested in prediction.
On the economics side, you can't avoid the "credibility revolution" literature (Mostly Harmless Econometrics, etc). ... | What are the major philosophical, methodological, and terminological differences between econometric | Of course, any broad statements are bound to be overly broad. But my experience has been that econometrics is concerned about causal relationships and statistics has become more interested in predicti | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
Of course, any broad statements are bound to be overly broad. But my experience has been that econometrics is concerned about causal relationships and statistics has become more interested... | What are the major philosophical, methodological, and terminological differences between econometric
Of course, any broad statements are bound to be overly broad. But my experience has been that econometrics is concerned about causal relationships and statistics has become more interested in predicti |
2,566 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | I've noticed that compared with what I'd call mainstream statistical science econometricians seem reluctant to use graphs, either schematic or data-based. The coverage of regression, which is naturally even more central in econometrics than elsewhere, is a major case in point. Modern introductions to regression by stat... | What are the major philosophical, methodological, and terminological differences between econometric | I've noticed that compared with what I'd call mainstream statistical science econometricians seem reluctant to use graphs, either schematic or data-based. The coverage of regression, which is naturall | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
I've noticed that compared with what I'd call mainstream statistical science econometricians seem reluctant to use graphs, either schematic or data-based. The coverage of regression, which... | What are the major philosophical, methodological, and terminological differences between econometric
I've noticed that compared with what I'd call mainstream statistical science econometricians seem reluctant to use graphs, either schematic or data-based. The coverage of regression, which is naturall |
2,567 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | One subtle difference is that economists sometimes ascribe meaning to the error terms in models. This is especially true among "structural" economists who believe that you can estimate structural parameters that represent interest or individual heterogeneity.
A class example of this is the probit. While statisticians a... | What are the major philosophical, methodological, and terminological differences between econometric | One subtle difference is that economists sometimes ascribe meaning to the error terms in models. This is especially true among "structural" economists who believe that you can estimate structural para | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
One subtle difference is that economists sometimes ascribe meaning to the error terms in models. This is especially true among "structural" economists who believe that you can estimate str... | What are the major philosophical, methodological, and terminological differences between econometric
One subtle difference is that economists sometimes ascribe meaning to the error terms in models. This is especially true among "structural" economists who believe that you can estimate structural para |
2,568 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | Unlike most other quantitative disciplines, economics deals with things at the MARGIN. That is, marginal utility, marginal rate of substitution, etc. In calculus terms, economics deals with "first" (and higher order derivatives).
Many statistical disciplines deal with non-derivative quantities such as means and varian... | What are the major philosophical, methodological, and terminological differences between econometric | Unlike most other quantitative disciplines, economics deals with things at the MARGIN. That is, marginal utility, marginal rate of substitution, etc. In calculus terms, economics deals with "first" (a | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
Unlike most other quantitative disciplines, economics deals with things at the MARGIN. That is, marginal utility, marginal rate of substitution, etc. In calculus terms, economics deals wit... | What are the major philosophical, methodological, and terminological differences between econometric
Unlike most other quantitative disciplines, economics deals with things at the MARGIN. That is, marginal utility, marginal rate of substitution, etc. In calculus terms, economics deals with "first" (a |
2,569 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | Econometricians are almost exclusively interested in causal inference, whereas statisticians also use models for predicting outcomes. As a result, econometricians focus more on exogeneity (as others have mentioned). Reduced form econometricians and structural econometricians get at this causal interpretations in diff... | What are the major philosophical, methodological, and terminological differences between econometric | Econometricians are almost exclusively interested in causal inference, whereas statisticians also use models for predicting outcomes. As a result, econometricians focus more on exogeneity (as others | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
Econometricians are almost exclusively interested in causal inference, whereas statisticians also use models for predicting outcomes. As a result, econometricians focus more on exogeneity... | What are the major philosophical, methodological, and terminological differences between econometric
Econometricians are almost exclusively interested in causal inference, whereas statisticians also use models for predicting outcomes. As a result, econometricians focus more on exogeneity (as others |
2,570 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | It is not econometrics, it is context. If your likelihood function does not have a unique optimum, it will concern both a statistician and an econometrician. Now if you propose an assumption that comes from economic theory and restricts the parametrization so that the parameter is identified, it might be called econome... | What are the major philosophical, methodological, and terminological differences between econometric | It is not econometrics, it is context. If your likelihood function does not have a unique optimum, it will concern both a statistician and an econometrician. Now if you propose an assumption that come | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
It is not econometrics, it is context. If your likelihood function does not have a unique optimum, it will concern both a statistician and an econometrician. Now if you propose an assumpti... | What are the major philosophical, methodological, and terminological differences between econometric
It is not econometrics, it is context. If your likelihood function does not have a unique optimum, it will concern both a statistician and an econometrician. Now if you propose an assumption that come |
2,571 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | As a statistician I think of this in more general terms. We have biometrics and econometrics. These are both areas where statistics is used to solve problems. With biometrics we are dealing with biological/medical problems whereas econometrics deals with economics. Otherwise they would be the same except that differ... | What are the major philosophical, methodological, and terminological differences between econometric | As a statistician I think of this in more general terms. We have biometrics and econometrics. These are both areas where statistics is used to solve problems. With biometrics we are dealing with bio | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
As a statistician I think of this in more general terms. We have biometrics and econometrics. These are both areas where statistics is used to solve problems. With biometrics we are deal... | What are the major philosophical, methodological, and terminological differences between econometric
As a statistician I think of this in more general terms. We have biometrics and econometrics. These are both areas where statistics is used to solve problems. With biometrics we are dealing with bio |
2,572 | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields? | I'd like to add one thing to give greater detail on something that was only mentioned in the other answers. Having taken classes in both areas, one of the main differences between the two is that statistics tends to stress the rigidity of the assumptions for regression models. The regression course I took in the statis... | What are the major philosophical, methodological, and terminological differences between econometric | I'd like to add one thing to give greater detail on something that was only mentioned in the other answers. Having taken classes in both areas, one of the main differences between the two is that stat | What are the major philosophical, methodological, and terminological differences between econometrics and other statistical fields?
I'd like to add one thing to give greater detail on something that was only mentioned in the other answers. Having taken classes in both areas, one of the main differences between the two ... | What are the major philosophical, methodological, and terminological differences between econometric
I'd like to add one thing to give greater detail on something that was only mentioned in the other answers. Having taken classes in both areas, one of the main differences between the two is that stat |
2,573 | Does no correlation imply no causality? | does an absence of correlation imply absence of causality?
No. Any controlled system is a counterexample.
Without causal relationships control is clearly impossible, but successful control means - roughly speaking - that some quantity is being maintained constant, which implies it won't be correlated with anything, in... | Does no correlation imply no causality? | does an absence of correlation imply absence of causality?
No. Any controlled system is a counterexample.
Without causal relationships control is clearly impossible, but successful control means - ro | Does no correlation imply no causality?
does an absence of correlation imply absence of causality?
No. Any controlled system is a counterexample.
Without causal relationships control is clearly impossible, but successful control means - roughly speaking - that some quantity is being maintained constant, which implies ... | Does no correlation imply no causality?
does an absence of correlation imply absence of causality?
No. Any controlled system is a counterexample.
Without causal relationships control is clearly impossible, but successful control means - ro |
2,574 | Does no correlation imply no causality? | No. Mainly because by correlation you most likely mean linear correlation. Two variables can be correlated nonlinearly, and may show no linear correlation. It's easy to construct an example like that, but I'll give you an example which is closer to your (narrower) question.
Let's look at the random variable $x$, and th... | Does no correlation imply no causality? | No. Mainly because by correlation you most likely mean linear correlation. Two variables can be correlated nonlinearly, and may show no linear correlation. It's easy to construct an example like that, | Does no correlation imply no causality?
No. Mainly because by correlation you most likely mean linear correlation. Two variables can be correlated nonlinearly, and may show no linear correlation. It's easy to construct an example like that, but I'll give you an example which is closer to your (narrower) question.
Let's... | Does no correlation imply no causality?
No. Mainly because by correlation you most likely mean linear correlation. Two variables can be correlated nonlinearly, and may show no linear correlation. It's easy to construct an example like that, |
2,575 | Does no correlation imply no causality? | No. In particular, random variables can be dependent but uncorrelated.
Here's an example. Suppose I have a machine that takes a single input $x ∈ [-1, 1]$ and produces a random number $Y$, which is equal to either $x$ or $-x$ with equal probability. Clearly $x$ causes $Y$. Now let $X$ be a random variable uniformly dis... | Does no correlation imply no causality? | No. In particular, random variables can be dependent but uncorrelated.
Here's an example. Suppose I have a machine that takes a single input $x ∈ [-1, 1]$ and produces a random number $Y$, which is eq | Does no correlation imply no causality?
No. In particular, random variables can be dependent but uncorrelated.
Here's an example. Suppose I have a machine that takes a single input $x ∈ [-1, 1]$ and produces a random number $Y$, which is equal to either $x$ or $-x$ with equal probability. Clearly $x$ causes $Y$. Now le... | Does no correlation imply no causality?
No. In particular, random variables can be dependent but uncorrelated.
Here's an example. Suppose I have a machine that takes a single input $x ∈ [-1, 1]$ and produces a random number $Y$, which is eq |
2,576 | Does no correlation imply no causality? | Maybe looking at it from a computational perspective will help.
As a concrete example, take a pseudorandom number generator.
Is there a causal relationship between the seed you set and the $k^\text{th}$ output from the generator?
Is there any measurable correlation? | Does no correlation imply no causality? | Maybe looking at it from a computational perspective will help.
As a concrete example, take a pseudorandom number generator.
Is there a causal relationship between the seed you set and the $k^\text{th | Does no correlation imply no causality?
Maybe looking at it from a computational perspective will help.
As a concrete example, take a pseudorandom number generator.
Is there a causal relationship between the seed you set and the $k^\text{th}$ output from the generator?
Is there any measurable correlation? | Does no correlation imply no causality?
Maybe looking at it from a computational perspective will help.
As a concrete example, take a pseudorandom number generator.
Is there a causal relationship between the seed you set and the $k^\text{th |
2,577 | Does no correlation imply no causality? | The better answer to the question is that correlation is a statistical, mathematical, and/or physical relationship while causation is a metaphysical relationship. You can't LOGICALLY get from correlation (or non-correlation) to causation, without a (large) set of assumptions binding the metaphysics to the physics. (One... | Does no correlation imply no causality? | The better answer to the question is that correlation is a statistical, mathematical, and/or physical relationship while causation is a metaphysical relationship. You can't LOGICALLY get from correlat | Does no correlation imply no causality?
The better answer to the question is that correlation is a statistical, mathematical, and/or physical relationship while causation is a metaphysical relationship. You can't LOGICALLY get from correlation (or non-correlation) to causation, without a (large) set of assumptions bind... | Does no correlation imply no causality?
The better answer to the question is that correlation is a statistical, mathematical, and/or physical relationship while causation is a metaphysical relationship. You can't LOGICALLY get from correlat |
2,578 | Does no correlation imply no causality? | Yes, contrary to previous replies. I'm going to take the question as nontechnical, particularly the definition of "correlation". Maybe I'm using it too broadly, but see my second bullet. I hope it will be considered appropriate to discuss other answers here, because they illuminate different portions of the question. ... | Does no correlation imply no causality? | Yes, contrary to previous replies. I'm going to take the question as nontechnical, particularly the definition of "correlation". Maybe I'm using it too broadly, but see my second bullet. I hope it wi | Does no correlation imply no causality?
Yes, contrary to previous replies. I'm going to take the question as nontechnical, particularly the definition of "correlation". Maybe I'm using it too broadly, but see my second bullet. I hope it will be considered appropriate to discuss other answers here, because they illumin... | Does no correlation imply no causality?
Yes, contrary to previous replies. I'm going to take the question as nontechnical, particularly the definition of "correlation". Maybe I'm using it too broadly, but see my second bullet. I hope it wi |
2,579 | What is translation invariance in computer vision and convolutional neural network? | You're on the right track.
Invariance means that you can recognize an object as an object, even when its appearance varies in some way. This is generally a good thing, because it preserves the object's identity, category, (etc) across changes in the specifics of the visual input, like relative positions of the viewer/c... | What is translation invariance in computer vision and convolutional neural network? | You're on the right track.
Invariance means that you can recognize an object as an object, even when its appearance varies in some way. This is generally a good thing, because it preserves the object' | What is translation invariance in computer vision and convolutional neural network?
You're on the right track.
Invariance means that you can recognize an object as an object, even when its appearance varies in some way. This is generally a good thing, because it preserves the object's identity, category, (etc) across c... | What is translation invariance in computer vision and convolutional neural network?
You're on the right track.
Invariance means that you can recognize an object as an object, even when its appearance varies in some way. This is generally a good thing, because it preserves the object' |
2,580 | What is translation invariance in computer vision and convolutional neural network? | I think there is some confusion about what is meant by translational invariance. Convolution provides translation equivariance meaning if an object in an image is at area A and through convolution a feature is detected at the output at area B, then the same feature would be detected when the object in the image is tran... | What is translation invariance in computer vision and convolutional neural network? | I think there is some confusion about what is meant by translational invariance. Convolution provides translation equivariance meaning if an object in an image is at area A and through convolution a f | What is translation invariance in computer vision and convolutional neural network?
I think there is some confusion about what is meant by translational invariance. Convolution provides translation equivariance meaning if an object in an image is at area A and through convolution a feature is detected at the output at ... | What is translation invariance in computer vision and convolutional neural network?
I think there is some confusion about what is meant by translational invariance. Convolution provides translation equivariance meaning if an object in an image is at area A and through convolution a f |
2,581 | What is translation invariance in computer vision and convolutional neural network? | @Santanu
While your answer is correct in part and leads to confusion. It is true that Convolutional layers themselves or output feature maps are translation equivariant. What the max-pooling layers do is provide some translation invariance as @Matt points out.
That is to say, the equivariance in the feature maps combi... | What is translation invariance in computer vision and convolutional neural network? | @Santanu
While your answer is correct in part and leads to confusion. It is true that Convolutional layers themselves or output feature maps are translation equivariant. What the max-pooling layers do | What is translation invariance in computer vision and convolutional neural network?
@Santanu
While your answer is correct in part and leads to confusion. It is true that Convolutional layers themselves or output feature maps are translation equivariant. What the max-pooling layers do is provide some translation invaria... | What is translation invariance in computer vision and convolutional neural network?
@Santanu
While your answer is correct in part and leads to confusion. It is true that Convolutional layers themselves or output feature maps are translation equivariant. What the max-pooling layers do |
2,582 | What is translation invariance in computer vision and convolutional neural network? | The answer is actually trickier than it appears at first. Generally, the translational invariance means that you would recognize the object regerdless of where it appears on the frame.
In the next picture in frame A and B you would recognize the word "stressed" if your vision supports translation invariance of words.
... | What is translation invariance in computer vision and convolutional neural network? | The answer is actually trickier than it appears at first. Generally, the translational invariance means that you would recognize the object regerdless of where it appears on the frame.
In the next pic | What is translation invariance in computer vision and convolutional neural network?
The answer is actually trickier than it appears at first. Generally, the translational invariance means that you would recognize the object regerdless of where it appears on the frame.
In the next picture in frame A and B you would reco... | What is translation invariance in computer vision and convolutional neural network?
The answer is actually trickier than it appears at first. Generally, the translational invariance means that you would recognize the object regerdless of where it appears on the frame.
In the next pic |
2,583 | What is translation invariance in computer vision and convolutional neural network? | I will answer you briefly,
translation invariant means that the algorithm will recognize the object even if you shifted its position from any place in the picture to any other place, lets say , we have a cat in photo with grass background , if you shifted the cat to the corner of the image or any other place , model st... | What is translation invariance in computer vision and convolutional neural network? | I will answer you briefly,
translation invariant means that the algorithm will recognize the object even if you shifted its position from any place in the picture to any other place, lets say , we hav | What is translation invariance in computer vision and convolutional neural network?
I will answer you briefly,
translation invariant means that the algorithm will recognize the object even if you shifted its position from any place in the picture to any other place, lets say , we have a cat in photo with grass backgrou... | What is translation invariance in computer vision and convolutional neural network?
I will answer you briefly,
translation invariant means that the algorithm will recognize the object even if you shifted its position from any place in the picture to any other place, lets say , we hav |
2,584 | What are good RMSE values? [duplicate] | I think you have two different types of questions there. One thing is what you ask in the title: "What are good RMSE values?" and another thing is how to compare models with different datasets using RMSE.
For the first, i.e., the question in the title, it is important to recall that RMSE has the same unit as the depend... | What are good RMSE values? [duplicate] | I think you have two different types of questions there. One thing is what you ask in the title: "What are good RMSE values?" and another thing is how to compare models with different datasets using R | What are good RMSE values? [duplicate]
I think you have two different types of questions there. One thing is what you ask in the title: "What are good RMSE values?" and another thing is how to compare models with different datasets using RMSE.
For the first, i.e., the question in the title, it is important to recall th... | What are good RMSE values? [duplicate]
I think you have two different types of questions there. One thing is what you ask in the title: "What are good RMSE values?" and another thing is how to compare models with different datasets using R |
2,585 | What are good RMSE values? [duplicate] | The RMSE for your training and your test sets should be very similar if you have built a good model. If the RMSE for the test set is much higher than that of the training set, it is likely that you've badly over fit the data, i.e. you've created a model that tests well in sample, but has little predictive value when t... | What are good RMSE values? [duplicate] | The RMSE for your training and your test sets should be very similar if you have built a good model. If the RMSE for the test set is much higher than that of the training set, it is likely that you'v | What are good RMSE values? [duplicate]
The RMSE for your training and your test sets should be very similar if you have built a good model. If the RMSE for the test set is much higher than that of the training set, it is likely that you've badly over fit the data, i.e. you've created a model that tests well in sample,... | What are good RMSE values? [duplicate]
The RMSE for your training and your test sets should be very similar if you have built a good model. If the RMSE for the test set is much higher than that of the training set, it is likely that you'v |
2,586 | What are good RMSE values? [duplicate] | Even though this is an old thread, I am hoping that my answer helps anyone who is looking for an answer to the same question.
When we talk about time series analysis, most of the time we mean the study of ARIMA models (and its variants). Hence I will start by assuming the same in my answer.
First of all, as the earlier... | What are good RMSE values? [duplicate] | Even though this is an old thread, I am hoping that my answer helps anyone who is looking for an answer to the same question.
When we talk about time series analysis, most of the time we mean the stud | What are good RMSE values? [duplicate]
Even though this is an old thread, I am hoping that my answer helps anyone who is looking for an answer to the same question.
When we talk about time series analysis, most of the time we mean the study of ARIMA models (and its variants). Hence I will start by assuming the same in ... | What are good RMSE values? [duplicate]
Even though this is an old thread, I am hoping that my answer helps anyone who is looking for an answer to the same question.
When we talk about time series analysis, most of the time we mean the stud |
2,587 | What are good RMSE values? [duplicate] | You can't fix particular threshold value for RMSE. We have to look at comparison of RMSE of both test and train datasets. If your model is good then your RMSE of test data is quite simillar to train dataset. Otherwise below conditions met.
RMSE of test > RMSE of train => OVER FITTING of the data.
RMSE of test < RMSE of... | What are good RMSE values? [duplicate] | You can't fix particular threshold value for RMSE. We have to look at comparison of RMSE of both test and train datasets. If your model is good then your RMSE of test data is quite simillar to train d | What are good RMSE values? [duplicate]
You can't fix particular threshold value for RMSE. We have to look at comparison of RMSE of both test and train datasets. If your model is good then your RMSE of test data is quite simillar to train dataset. Otherwise below conditions met.
RMSE of test > RMSE of train => OVER FITT... | What are good RMSE values? [duplicate]
You can't fix particular threshold value for RMSE. We have to look at comparison of RMSE of both test and train datasets. If your model is good then your RMSE of test data is quite simillar to train d |
2,588 | What are good RMSE values? [duplicate] | Personally I like the RMSE / standard deviation approach. Range is misleading, you could have a skewed distribution or outliers, whereas standard deviation takes care of this. Similarly, RMSE / mean is totally wrong - what if your mean is zero? However, this does not help to tell you whether you have a good model or no... | What are good RMSE values? [duplicate] | Personally I like the RMSE / standard deviation approach. Range is misleading, you could have a skewed distribution or outliers, whereas standard deviation takes care of this. Similarly, RMSE / mean i | What are good RMSE values? [duplicate]
Personally I like the RMSE / standard deviation approach. Range is misleading, you could have a skewed distribution or outliers, whereas standard deviation takes care of this. Similarly, RMSE / mean is totally wrong - what if your mean is zero? However, this does not help to tell ... | What are good RMSE values? [duplicate]
Personally I like the RMSE / standard deviation approach. Range is misleading, you could have a skewed distribution or outliers, whereas standard deviation takes care of this. Similarly, RMSE / mean i |
2,589 | Choosing a clustering method | There is no definitive answer to your question, as even within the same method the choice of the distance to represent individuals (dis)similarity may yield different result, e.g. when using euclidean vs. squared euclidean in hierarchical clustering. As an other example, for binary data, you can choose the Jaccard inde... | Choosing a clustering method | There is no definitive answer to your question, as even within the same method the choice of the distance to represent individuals (dis)similarity may yield different result, e.g. when using euclidean | Choosing a clustering method
There is no definitive answer to your question, as even within the same method the choice of the distance to represent individuals (dis)similarity may yield different result, e.g. when using euclidean vs. squared euclidean in hierarchical clustering. As an other example, for binary data, yo... | Choosing a clustering method
There is no definitive answer to your question, as even within the same method the choice of the distance to represent individuals (dis)similarity may yield different result, e.g. when using euclidean |
2,590 | Choosing a clustering method | A quote from Hastie, Tibshirani and Friedman,
Elements of Statistical Learning,
p. 506:
"An appropriate dissimilarity measure
is far more important in obtaining
success with clustering than choice
of clustering algorithm. This aspect
of the problem ...
depends on domain specific knowledge
and is less amen... | Choosing a clustering method | A quote from Hastie, Tibshirani and Friedman,
Elements of Statistical Learning,
p. 506:
"An appropriate dissimilarity measure
is far more important in obtaining
success with clustering than choic | Choosing a clustering method
A quote from Hastie, Tibshirani and Friedman,
Elements of Statistical Learning,
p. 506:
"An appropriate dissimilarity measure
is far more important in obtaining
success with clustering than choice
of clustering algorithm. This aspect
of the problem ...
depends on domain specific... | Choosing a clustering method
A quote from Hastie, Tibshirani and Friedman,
Elements of Statistical Learning,
p. 506:
"An appropriate dissimilarity measure
is far more important in obtaining
success with clustering than choic |
2,591 | Choosing a clustering method | You can't know in advance which clustering algorithm would be better, but there are some clues, for example if you want to cluster images there are certain algorithms you should try first like Fuzzy Art, or if you want to group faces you should start with (GGCI) global geometric clustering for image.
Anyway this does n... | Choosing a clustering method | You can't know in advance which clustering algorithm would be better, but there are some clues, for example if you want to cluster images there are certain algorithms you should try first like Fuzzy A | Choosing a clustering method
You can't know in advance which clustering algorithm would be better, but there are some clues, for example if you want to cluster images there are certain algorithms you should try first like Fuzzy Art, or if you want to group faces you should start with (GGCI) global geometric clustering ... | Choosing a clustering method
You can't know in advance which clustering algorithm would be better, but there are some clues, for example if you want to cluster images there are certain algorithms you should try first like Fuzzy A |
2,592 | Choosing a clustering method | Choosing the right distance is not an elementary task. When we want to make a cluster analysis on a data set, different results could appear using different distances, so it's very important to be careful in which distance to choose because we can make a false good artefact that capture well the variability, but actual... | Choosing a clustering method | Choosing the right distance is not an elementary task. When we want to make a cluster analysis on a data set, different results could appear using different distances, so it's very important to be car | Choosing a clustering method
Choosing the right distance is not an elementary task. When we want to make a cluster analysis on a data set, different results could appear using different distances, so it's very important to be careful in which distance to choose because we can make a false good artefact that capture wel... | Choosing a clustering method
Choosing the right distance is not an elementary task. When we want to make a cluster analysis on a data set, different results could appear using different distances, so it's very important to be car |
2,593 | Choosing a clustering method | Here is a summary of several clustering algorithms that can help to answer the question
"which clustering technique i should use?"
There is no objectively "correct" clustering algorithm Ref
Clustering algorithms can be categorized based on their "cluster model". An algorithm designed for a particular kind of model ... | Choosing a clustering method | Here is a summary of several clustering algorithms that can help to answer the question
"which clustering technique i should use?"
There is no objectively "correct" clustering algorithm Ref
Cluste | Choosing a clustering method
Here is a summary of several clustering algorithms that can help to answer the question
"which clustering technique i should use?"
There is no objectively "correct" clustering algorithm Ref
Clustering algorithms can be categorized based on their "cluster model". An algorithm designed fo... | Choosing a clustering method
Here is a summary of several clustering algorithms that can help to answer the question
"which clustering technique i should use?"
There is no objectively "correct" clustering algorithm Ref
Cluste |
2,594 | Choosing a clustering method | As far as I'm concerned, if you want a safe choice, spectral clustering methods have been achieving the highest accuracy rates in recent years - at least in image clustering.
As for the distance metric, it depends a lot on how your data is organized. The safe choice is the simple euclidean distance but if you know your... | Choosing a clustering method | As far as I'm concerned, if you want a safe choice, spectral clustering methods have been achieving the highest accuracy rates in recent years - at least in image clustering.
As for the distance metri | Choosing a clustering method
As far as I'm concerned, if you want a safe choice, spectral clustering methods have been achieving the highest accuracy rates in recent years - at least in image clustering.
As for the distance metric, it depends a lot on how your data is organized. The safe choice is the simple euclidean ... | Choosing a clustering method
As far as I'm concerned, if you want a safe choice, spectral clustering methods have been achieving the highest accuracy rates in recent years - at least in image clustering.
As for the distance metri |
2,595 | Rules of thumb for minimum sample size for multiple regression | I'm not a fan of simple formulas for generating minimum sample sizes.
At the very least, any formula should consider effect size and the questions of interest.
And the difference between either side of a cut-off is minimal.
Sample size as optimisation problem
Bigger samples are better.
Sample size is often determined ... | Rules of thumb for minimum sample size for multiple regression | I'm not a fan of simple formulas for generating minimum sample sizes.
At the very least, any formula should consider effect size and the questions of interest.
And the difference between either side o | Rules of thumb for minimum sample size for multiple regression
I'm not a fan of simple formulas for generating minimum sample sizes.
At the very least, any formula should consider effect size and the questions of interest.
And the difference between either side of a cut-off is minimal.
Sample size as optimisation probl... | Rules of thumb for minimum sample size for multiple regression
I'm not a fan of simple formulas for generating minimum sample sizes.
At the very least, any formula should consider effect size and the questions of interest.
And the difference between either side o |
2,596 | Rules of thumb for minimum sample size for multiple regression | I don't prefer to think of this as a power issue, but rather ask the question "how large should $n$ be so that the apparent $R^2$ can be trusted"? One way to approach that is to consider the ratio or difference between $R^2$ and $R_{adj}^{2}$, the latter being the adjusted $R^2$ given by $1 - (1 - R^{2})\frac{n-1}{n-p... | Rules of thumb for minimum sample size for multiple regression | I don't prefer to think of this as a power issue, but rather ask the question "how large should $n$ be so that the apparent $R^2$ can be trusted"? One way to approach that is to consider the ratio or | Rules of thumb for minimum sample size for multiple regression
I don't prefer to think of this as a power issue, but rather ask the question "how large should $n$ be so that the apparent $R^2$ can be trusted"? One way to approach that is to consider the ratio or difference between $R^2$ and $R_{adj}^{2}$, the latter b... | Rules of thumb for minimum sample size for multiple regression
I don't prefer to think of this as a power issue, but rather ask the question "how large should $n$ be so that the apparent $R^2$ can be trusted"? One way to approach that is to consider the ratio or |
2,597 | Rules of thumb for minimum sample size for multiple regression | (+1) for indeed a crucial, in my opinion, question.
In macro-econometrics you usually have much smaller sample sizes than in micro, financial or sociological experiments. A researcher feels quite well when on can provide at least feasible estimations. My personal least possible rule of thumb is $4\cdot m$ ($4$ degrees... | Rules of thumb for minimum sample size for multiple regression | (+1) for indeed a crucial, in my opinion, question.
In macro-econometrics you usually have much smaller sample sizes than in micro, financial or sociological experiments. A researcher feels quite wel | Rules of thumb for minimum sample size for multiple regression
(+1) for indeed a crucial, in my opinion, question.
In macro-econometrics you usually have much smaller sample sizes than in micro, financial or sociological experiments. A researcher feels quite well when on can provide at least feasible estimations. My p... | Rules of thumb for minimum sample size for multiple regression
(+1) for indeed a crucial, in my opinion, question.
In macro-econometrics you usually have much smaller sample sizes than in micro, financial or sociological experiments. A researcher feels quite wel |
2,598 | Rules of thumb for minimum sample size for multiple regression | Your rule of thumb is not particularly good if $m$ is very large. Take $m=500$: your rule says its ok to fit $500$ variables with only $600$ observations. I hardly think so!
For multiple regression, you have some theory to suggest a minimum sample size. If you are going to be using ordinary least squares, then one o... | Rules of thumb for minimum sample size for multiple regression | Your rule of thumb is not particularly good if $m$ is very large. Take $m=500$: your rule says its ok to fit $500$ variables with only $600$ observations. I hardly think so!
For multiple regression, | Rules of thumb for minimum sample size for multiple regression
Your rule of thumb is not particularly good if $m$ is very large. Take $m=500$: your rule says its ok to fit $500$ variables with only $600$ observations. I hardly think so!
For multiple regression, you have some theory to suggest a minimum sample size. ... | Rules of thumb for minimum sample size for multiple regression
Your rule of thumb is not particularly good if $m$ is very large. Take $m=500$: your rule says its ok to fit $500$ variables with only $600$ observations. I hardly think so!
For multiple regression, |
2,599 | Rules of thumb for minimum sample size for multiple regression | In Psychology:
Green (1991) indicates that $N > 50 + 8m$ (where m is the number of independent variables) is needed for testing multiple correlation and $N > 104 + m$ for testing individual predictors.
Other rules that can be used are...
Harris (1985) says that the number of participants should exceed the number of p... | Rules of thumb for minimum sample size for multiple regression | In Psychology:
Green (1991) indicates that $N > 50 + 8m$ (where m is the number of independent variables) is needed for testing multiple correlation and $N > 104 + m$ for testing individual predictor | Rules of thumb for minimum sample size for multiple regression
In Psychology:
Green (1991) indicates that $N > 50 + 8m$ (where m is the number of independent variables) is needed for testing multiple correlation and $N > 104 + m$ for testing individual predictors.
Other rules that can be used are...
Harris (1985) say... | Rules of thumb for minimum sample size for multiple regression
In Psychology:
Green (1991) indicates that $N > 50 + 8m$ (where m is the number of independent variables) is needed for testing multiple correlation and $N > 104 + m$ for testing individual predictor |
2,600 | Rules of thumb for minimum sample size for multiple regression | I agree that power calculators are useful, especially to see the effect of different factors on the power. In that sense, calculators that include more input information are much better. For linear regression, I like the regression calculator here which includes factors such as error in Xs, correlation between Xs, and ... | Rules of thumb for minimum sample size for multiple regression | I agree that power calculators are useful, especially to see the effect of different factors on the power. In that sense, calculators that include more input information are much better. For linear re | Rules of thumb for minimum sample size for multiple regression
I agree that power calculators are useful, especially to see the effect of different factors on the power. In that sense, calculators that include more input information are much better. For linear regression, I like the regression calculator here which inc... | Rules of thumb for minimum sample size for multiple regression
I agree that power calculators are useful, especially to see the effect of different factors on the power. In that sense, calculators that include more input information are much better. For linear re |
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