idx int64 1 56k | question stringlengths 15 155 | answer stringlengths 2 29.2k ⌀ | question_cut stringlengths 15 100 | answer_cut stringlengths 2 200 ⌀ | conversation stringlengths 47 29.3k | conversation_cut stringlengths 47 301 |
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3,201 | Why is the validation accuracy fluctuating? | Adding to the answer by @dk14 . If you are still seeing fluctuations after properly regularising your model, these could be the possible reasons:
Using a random sample from your validation set: It means your validation set at each evaluation step is different, so is your validation-loss.
Using a weighted loss-functio... | Why is the validation accuracy fluctuating? | Adding to the answer by @dk14 . If you are still seeing fluctuations after properly regularising your model, these could be the possible reasons:
Using a random sample from your validation set: It me | Why is the validation accuracy fluctuating?
Adding to the answer by @dk14 . If you are still seeing fluctuations after properly regularising your model, these could be the possible reasons:
Using a random sample from your validation set: It means your validation set at each evaluation step is different, so is your val... | Why is the validation accuracy fluctuating?
Adding to the answer by @dk14 . If you are still seeing fluctuations after properly regularising your model, these could be the possible reasons:
Using a random sample from your validation set: It me |
3,202 | Why is the validation accuracy fluctuating? | Your validation accuracy on a binary classification problem (I assume) is "fluctuating" around 50%, that means your model is giving completely random predictions (sometimes it guesses correctly few samples more, sometimes a few samples less). Generally, your model is not better than flipping a coin.
The reason the vali... | Why is the validation accuracy fluctuating? | Your validation accuracy on a binary classification problem (I assume) is "fluctuating" around 50%, that means your model is giving completely random predictions (sometimes it guesses correctly few sa | Why is the validation accuracy fluctuating?
Your validation accuracy on a binary classification problem (I assume) is "fluctuating" around 50%, that means your model is giving completely random predictions (sometimes it guesses correctly few samples more, sometimes a few samples less). Generally, your model is not bett... | Why is the validation accuracy fluctuating?
Your validation accuracy on a binary classification problem (I assume) is "fluctuating" around 50%, that means your model is giving completely random predictions (sometimes it guesses correctly few sa |
3,203 | Why is the validation accuracy fluctuating? | Definitely over-fitting. The gap between accuracy on training data and test data shows you have over fitted on training. Maybe regularization can help. | Why is the validation accuracy fluctuating? | Definitely over-fitting. The gap between accuracy on training data and test data shows you have over fitted on training. Maybe regularization can help. | Why is the validation accuracy fluctuating?
Definitely over-fitting. The gap between accuracy on training data and test data shows you have over fitted on training. Maybe regularization can help. | Why is the validation accuracy fluctuating?
Definitely over-fitting. The gap between accuracy on training data and test data shows you have over fitted on training. Maybe regularization can help. |
3,204 | Why is the validation accuracy fluctuating? | There are few ways to try in your situation. Firstly try to increase the batch size, which helps the mini-batch SGD less wandering wildly. Secondly tuning the learning rate, probably set it smaller. Thirdly, try different optimizer, for instance Adam or RMSProp which are able to adapt learning rates for wrt features. I... | Why is the validation accuracy fluctuating? | There are few ways to try in your situation. Firstly try to increase the batch size, which helps the mini-batch SGD less wandering wildly. Secondly tuning the learning rate, probably set it smaller. T | Why is the validation accuracy fluctuating?
There are few ways to try in your situation. Firstly try to increase the batch size, which helps the mini-batch SGD less wandering wildly. Secondly tuning the learning rate, probably set it smaller. Thirdly, try different optimizer, for instance Adam or RMSProp which are able... | Why is the validation accuracy fluctuating?
There are few ways to try in your situation. Firstly try to increase the batch size, which helps the mini-batch SGD less wandering wildly. Secondly tuning the learning rate, probably set it smaller. T |
3,205 | Why is the validation accuracy fluctuating? | Have you tried a smaller network? Considering your training accuracy can reach >.99, your network seems have enough connections to fully model your data, but you may have extraneous connections that are learning randomly (i.e. overfitting).
In my experience, I've gotten the holdout validation accuracy to stabilize wit... | Why is the validation accuracy fluctuating? | Have you tried a smaller network? Considering your training accuracy can reach >.99, your network seems have enough connections to fully model your data, but you may have extraneous connections that a | Why is the validation accuracy fluctuating?
Have you tried a smaller network? Considering your training accuracy can reach >.99, your network seems have enough connections to fully model your data, but you may have extraneous connections that are learning randomly (i.e. overfitting).
In my experience, I've gotten the ... | Why is the validation accuracy fluctuating?
Have you tried a smaller network? Considering your training accuracy can reach >.99, your network seems have enough connections to fully model your data, but you may have extraneous connections that a |
3,206 | What is the difference between a neural network and a deep belief network? | "Neural networks" is a term usually used to refer to feedforward neural networks. Deep Neural Networks are feedforward Neural Networks with many layers.
A Deep belief network is not the same as a Deep Neural Network.
As you have pointed out a deep belief network has undirected connections between some layers. This mea... | What is the difference between a neural network and a deep belief network? | "Neural networks" is a term usually used to refer to feedforward neural networks. Deep Neural Networks are feedforward Neural Networks with many layers.
A Deep belief network is not the same as a Dee | What is the difference between a neural network and a deep belief network?
"Neural networks" is a term usually used to refer to feedforward neural networks. Deep Neural Networks are feedforward Neural Networks with many layers.
A Deep belief network is not the same as a Deep Neural Network.
As you have pointed out a d... | What is the difference between a neural network and a deep belief network?
"Neural networks" is a term usually used to refer to feedforward neural networks. Deep Neural Networks are feedforward Neural Networks with many layers.
A Deep belief network is not the same as a Dee |
3,207 | What is the difference between a neural network and a deep belief network? | "A Deep Neural Network is a feed-forward, artificial neural network that has more than one layer of hidden units between its inputs and its outputs. Each hidden unit, $j$, typically uses the logistic function to map its total input from the layer below,$x_j$, to the scalar state, $y_j$ that it sends to the layer above.... | What is the difference between a neural network and a deep belief network? | "A Deep Neural Network is a feed-forward, artificial neural network that has more than one layer of hidden units between its inputs and its outputs. Each hidden unit, $j$, typically uses the logistic | What is the difference between a neural network and a deep belief network?
"A Deep Neural Network is a feed-forward, artificial neural network that has more than one layer of hidden units between its inputs and its outputs. Each hidden unit, $j$, typically uses the logistic function to map its total input from the laye... | What is the difference between a neural network and a deep belief network?
"A Deep Neural Network is a feed-forward, artificial neural network that has more than one layer of hidden units between its inputs and its outputs. Each hidden unit, $j$, typically uses the logistic |
3,208 | Proper way of using recurrent neural network for time series analysis | What you describe is in fact a "sliding time window" approach and is different to recurrent networks. You can use this technique with any regression algorithm. There is a huge limitation to this approach: events in the inputs can only be correlatd with other inputs/outputs which lie at most t timesteps apart, where t i... | Proper way of using recurrent neural network for time series analysis | What you describe is in fact a "sliding time window" approach and is different to recurrent networks. You can use this technique with any regression algorithm. There is a huge limitation to this appro | Proper way of using recurrent neural network for time series analysis
What you describe is in fact a "sliding time window" approach and is different to recurrent networks. You can use this technique with any regression algorithm. There is a huge limitation to this approach: events in the inputs can only be correlatd wi... | Proper way of using recurrent neural network for time series analysis
What you describe is in fact a "sliding time window" approach and is different to recurrent networks. You can use this technique with any regression algorithm. There is a huge limitation to this appro |
3,209 | Proper way of using recurrent neural network for time series analysis | You may also consider simply using a number of transforms of time series for the input data. Just for one example, the inputs could be:
the most recent interval value
(7)
the next most recent interval
value (6)
the delta between most
recent and next most recent (7-6=1)
the third most recent interval
valu... | Proper way of using recurrent neural network for time series analysis | You may also consider simply using a number of transforms of time series for the input data. Just for one example, the inputs could be:
the most recent interval value
(7)
the next most recent inter | Proper way of using recurrent neural network for time series analysis
You may also consider simply using a number of transforms of time series for the input data. Just for one example, the inputs could be:
the most recent interval value
(7)
the next most recent interval
value (6)
the delta between most
recen... | Proper way of using recurrent neural network for time series analysis
You may also consider simply using a number of transforms of time series for the input data. Just for one example, the inputs could be:
the most recent interval value
(7)
the next most recent inter |
3,210 | Proper way of using recurrent neural network for time series analysis | Another possibility are Historical Consistent Neural Networks (HCNN). This architecture might be more appropriate for the above mentioned setup because they eliminate the often arbitrary distinction between input- and output-variables and instead try to replicate the full underlying dynamics of the whole system via tra... | Proper way of using recurrent neural network for time series analysis | Another possibility are Historical Consistent Neural Networks (HCNN). This architecture might be more appropriate for the above mentioned setup because they eliminate the often arbitrary distinction b | Proper way of using recurrent neural network for time series analysis
Another possibility are Historical Consistent Neural Networks (HCNN). This architecture might be more appropriate for the above mentioned setup because they eliminate the often arbitrary distinction between input- and output-variables and instead try... | Proper way of using recurrent neural network for time series analysis
Another possibility are Historical Consistent Neural Networks (HCNN). This architecture might be more appropriate for the above mentioned setup because they eliminate the often arbitrary distinction b |
3,211 | Regression with multiple dependent variables? | Yes, it is possible. What you're interested is is called "Multivariate Multiple Regression" or just "Multivariate Regression". I don't know what software you are using, but you can do this in R.
Here's a link that provides examples. | Regression with multiple dependent variables? | Yes, it is possible. What you're interested is is called "Multivariate Multiple Regression" or just "Multivariate Regression". I don't know what software you are using, but you can do this in R.
Her | Regression with multiple dependent variables?
Yes, it is possible. What you're interested is is called "Multivariate Multiple Regression" or just "Multivariate Regression". I don't know what software you are using, but you can do this in R.
Here's a link that provides examples. | Regression with multiple dependent variables?
Yes, it is possible. What you're interested is is called "Multivariate Multiple Regression" or just "Multivariate Regression". I don't know what software you are using, but you can do this in R.
Her |
3,212 | Regression with multiple dependent variables? | @Brett's response is fine.
If you are interested in describing your two-block structure, you could also use PLS regression. Basically, it is a regression framework which relies on the idea of building successive (orthogonal) linear combinations of the variables belonging to each block such that their covariance is max... | Regression with multiple dependent variables? | @Brett's response is fine.
If you are interested in describing your two-block structure, you could also use PLS regression. Basically, it is a regression framework which relies on the idea of buildin | Regression with multiple dependent variables?
@Brett's response is fine.
If you are interested in describing your two-block structure, you could also use PLS regression. Basically, it is a regression framework which relies on the idea of building successive (orthogonal) linear combinations of the variables belonging t... | Regression with multiple dependent variables?
@Brett's response is fine.
If you are interested in describing your two-block structure, you could also use PLS regression. Basically, it is a regression framework which relies on the idea of buildin |
3,213 | Regression with multiple dependent variables? | Multivariate regression is done in SPSS using the GLM-multivariate option.
Put all your outcomes (DVs) into the outcomes box, but all your continuous predictors into the covariates box. You don't need anything in the factors box. Look at the multivariate tests. The univariate tests will be the same as separate multipl... | Regression with multiple dependent variables? | Multivariate regression is done in SPSS using the GLM-multivariate option.
Put all your outcomes (DVs) into the outcomes box, but all your continuous predictors into the covariates box. You don't need | Regression with multiple dependent variables?
Multivariate regression is done in SPSS using the GLM-multivariate option.
Put all your outcomes (DVs) into the outcomes box, but all your continuous predictors into the covariates box. You don't need anything in the factors box. Look at the multivariate tests. The univari... | Regression with multiple dependent variables?
Multivariate regression is done in SPSS using the GLM-multivariate option.
Put all your outcomes (DVs) into the outcomes box, but all your continuous predictors into the covariates box. You don't need |
3,214 | Regression with multiple dependent variables? | I would do this by first transforming the regression variables to PCA calculated variables, and then I would to the regression with the PCA calculated variables. Of course I would store the eigenvectors to be able to calculate the corresponding pca values when I have a new instance I wanna classify. | Regression with multiple dependent variables? | I would do this by first transforming the regression variables to PCA calculated variables, and then I would to the regression with the PCA calculated variables. Of course I would store the eigenvecto | Regression with multiple dependent variables?
I would do this by first transforming the regression variables to PCA calculated variables, and then I would to the regression with the PCA calculated variables. Of course I would store the eigenvectors to be able to calculate the corresponding pca values when I have a new ... | Regression with multiple dependent variables?
I would do this by first transforming the regression variables to PCA calculated variables, and then I would to the regression with the PCA calculated variables. Of course I would store the eigenvecto |
3,215 | Regression with multiple dependent variables? | As mentionned by caracal, you can use mvtnorm package in R. Assuming you made a lm model (named "model") of one of the response in your model, and called it "model", here is how to obtain the multivariate predictive distribution of several response "resp1", "resp2", "resp3" stored in a matrix form Y:
library(mvtnorm)
m... | Regression with multiple dependent variables? | As mentionned by caracal, you can use mvtnorm package in R. Assuming you made a lm model (named "model") of one of the response in your model, and called it "model", here is how to obtain the multivar | Regression with multiple dependent variables?
As mentionned by caracal, you can use mvtnorm package in R. Assuming you made a lm model (named "model") of one of the response in your model, and called it "model", here is how to obtain the multivariate predictive distribution of several response "resp1", "resp2", "resp3"... | Regression with multiple dependent variables?
As mentionned by caracal, you can use mvtnorm package in R. Assuming you made a lm model (named "model") of one of the response in your model, and called it "model", here is how to obtain the multivar |
3,216 | Regression with multiple dependent variables? | Did you already come across the term "canonical correlation"? There you have sets of variables on the independent as well as on the dependent side. But maybe there are more modern concepts available, the descriptions I have are all of the eighties/nineties... | Regression with multiple dependent variables? | Did you already come across the term "canonical correlation"? There you have sets of variables on the independent as well as on the dependent side. But maybe there are more modern concepts available, | Regression with multiple dependent variables?
Did you already come across the term "canonical correlation"? There you have sets of variables on the independent as well as on the dependent side. But maybe there are more modern concepts available, the descriptions I have are all of the eighties/nineties... | Regression with multiple dependent variables?
Did you already come across the term "canonical correlation"? There you have sets of variables on the independent as well as on the dependent side. But maybe there are more modern concepts available, |
3,217 | Regression with multiple dependent variables? | For Bayesian multivariate regression, one can use R package BNSP. For example, the dataset ami that comes with the package includes 3 responses and 3 covariates.
# First load the package and dataset
require(BNSP)
data(ami)
# Second, centre and scale variables -
# this is specific to the dataset
sc <- function(x){retu... | Regression with multiple dependent variables? | For Bayesian multivariate regression, one can use R package BNSP. For example, the dataset ami that comes with the package includes 3 responses and 3 covariates.
# First load the package and dataset
r | Regression with multiple dependent variables?
For Bayesian multivariate regression, one can use R package BNSP. For example, the dataset ami that comes with the package includes 3 responses and 3 covariates.
# First load the package and dataset
require(BNSP)
data(ami)
# Second, centre and scale variables -
# this is ... | Regression with multiple dependent variables?
For Bayesian multivariate regression, one can use R package BNSP. For example, the dataset ami that comes with the package includes 3 responses and 3 covariates.
# First load the package and dataset
r |
3,218 | Regression with multiple dependent variables? | It's called structural equation model or simultaneous equation model. | Regression with multiple dependent variables? | It's called structural equation model or simultaneous equation model. | Regression with multiple dependent variables?
It's called structural equation model or simultaneous equation model. | Regression with multiple dependent variables?
It's called structural equation model or simultaneous equation model. |
3,219 | What are the worst (commonly adopted) ideas/principles in statistics? | I'll present one novice error (in this answer) and perhaps one error committed by more seasoned people.
Very often, even on this website, I see people lamenting that their data are not normally distributed and so t-tests or linear regression are out of the question. Even stranger, I will see people try to rationalize ... | What are the worst (commonly adopted) ideas/principles in statistics? | I'll present one novice error (in this answer) and perhaps one error committed by more seasoned people.
Very often, even on this website, I see people lamenting that their data are not normally distri | What are the worst (commonly adopted) ideas/principles in statistics?
I'll present one novice error (in this answer) and perhaps one error committed by more seasoned people.
Very often, even on this website, I see people lamenting that their data are not normally distributed and so t-tests or linear regression are out ... | What are the worst (commonly adopted) ideas/principles in statistics?
I'll present one novice error (in this answer) and perhaps one error committed by more seasoned people.
Very often, even on this website, I see people lamenting that their data are not normally distri |
3,220 | What are the worst (commonly adopted) ideas/principles in statistics? | Post hoc power analysis
That is, using power analysis after a study has been completed rather than before, and in particular plugging in the observed effect size estimate, sample size, etc.
Some people have the intuition that post hoc power analysis could be informative because it could help explain why they attained a... | What are the worst (commonly adopted) ideas/principles in statistics? | Post hoc power analysis
That is, using power analysis after a study has been completed rather than before, and in particular plugging in the observed effect size estimate, sample size, etc.
Some peopl | What are the worst (commonly adopted) ideas/principles in statistics?
Post hoc power analysis
That is, using power analysis after a study has been completed rather than before, and in particular plugging in the observed effect size estimate, sample size, etc.
Some people have the intuition that post hoc power analysis ... | What are the worst (commonly adopted) ideas/principles in statistics?
Post hoc power analysis
That is, using power analysis after a study has been completed rather than before, and in particular plugging in the observed effect size estimate, sample size, etc.
Some peopl |
3,221 | What are the worst (commonly adopted) ideas/principles in statistics? | The idea that because something is not statistically significant, it is not interesting and should be ignored. | What are the worst (commonly adopted) ideas/principles in statistics? | The idea that because something is not statistically significant, it is not interesting and should be ignored. | What are the worst (commonly adopted) ideas/principles in statistics?
The idea that because something is not statistically significant, it is not interesting and should be ignored. | What are the worst (commonly adopted) ideas/principles in statistics?
The idea that because something is not statistically significant, it is not interesting and should be ignored. |
3,222 | What are the worst (commonly adopted) ideas/principles in statistics? | Removing Outliers
It seems that many individuals have the idea that they not only can, but should disregard data points that are some number of standard deviations away from the mean. Even when there is no reason to suspect that the observation is invalid, or any conscious justification for identifying/removing outlier... | What are the worst (commonly adopted) ideas/principles in statistics? | Removing Outliers
It seems that many individuals have the idea that they not only can, but should disregard data points that are some number of standard deviations away from the mean. Even when there | What are the worst (commonly adopted) ideas/principles in statistics?
Removing Outliers
It seems that many individuals have the idea that they not only can, but should disregard data points that are some number of standard deviations away from the mean. Even when there is no reason to suspect that the observation is in... | What are the worst (commonly adopted) ideas/principles in statistics?
Removing Outliers
It seems that many individuals have the idea that they not only can, but should disregard data points that are some number of standard deviations away from the mean. Even when there |
3,223 | What are the worst (commonly adopted) ideas/principles in statistics? | Not addressing multiple hypothesis testing problems.
Just because you aren't performing a t.test on 1,000,000 genes doesn't mean you're safe from it. One example of a field it notably pops up is in studies that test an effect conditional on a previous effect being significant. Often in experiments the authors identify ... | What are the worst (commonly adopted) ideas/principles in statistics? | Not addressing multiple hypothesis testing problems.
Just because you aren't performing a t.test on 1,000,000 genes doesn't mean you're safe from it. One example of a field it notably pops up is in st | What are the worst (commonly adopted) ideas/principles in statistics?
Not addressing multiple hypothesis testing problems.
Just because you aren't performing a t.test on 1,000,000 genes doesn't mean you're safe from it. One example of a field it notably pops up is in studies that test an effect conditional on a previou... | What are the worst (commonly adopted) ideas/principles in statistics?
Not addressing multiple hypothesis testing problems.
Just because you aren't performing a t.test on 1,000,000 genes doesn't mean you're safe from it. One example of a field it notably pops up is in st |
3,224 | What are the worst (commonly adopted) ideas/principles in statistics? | This seems like low hanging fruit, but stepwise regression is one error which I see pretty frequently even from some stats people. Even if you haven't read some of the very well-written answers on this site which address the approach and its flaws, I think if you just took a moment to understand what is happening (tha... | What are the worst (commonly adopted) ideas/principles in statistics? | This seems like low hanging fruit, but stepwise regression is one error which I see pretty frequently even from some stats people. Even if you haven't read some of the very well-written answers on th | What are the worst (commonly adopted) ideas/principles in statistics?
This seems like low hanging fruit, but stepwise regression is one error which I see pretty frequently even from some stats people. Even if you haven't read some of the very well-written answers on this site which address the approach and its flaws, ... | What are the worst (commonly adopted) ideas/principles in statistics?
This seems like low hanging fruit, but stepwise regression is one error which I see pretty frequently even from some stats people. Even if you haven't read some of the very well-written answers on th |
3,225 | What are the worst (commonly adopted) ideas/principles in statistics? | Regression towards the mean is a far more common problem than is often realised.
It is also one of those things that is actually quite simple but appears to be quite nebulous on closer inspection, and this is partly due to the narrow way that it is usually taught. Sometimes it is attributed entirely to measurement err... | What are the worst (commonly adopted) ideas/principles in statistics? | Regression towards the mean is a far more common problem than is often realised.
It is also one of those things that is actually quite simple but appears to be quite nebulous on closer inspection, an | What are the worst (commonly adopted) ideas/principles in statistics?
Regression towards the mean is a far more common problem than is often realised.
It is also one of those things that is actually quite simple but appears to be quite nebulous on closer inspection, and this is partly due to the narrow way that it is ... | What are the worst (commonly adopted) ideas/principles in statistics?
Regression towards the mean is a far more common problem than is often realised.
It is also one of those things that is actually quite simple but appears to be quite nebulous on closer inspection, an |
3,226 | What are the worst (commonly adopted) ideas/principles in statistics? | You have a nice answer to one that I posted a few weeks ago.
Debunking wrong CLT statement
False claim: the central limit theorem says that the empirical distribution converges to a normal distribution.
As the answers to my question show, that claim is utterly preposterous (unless the population is normal), yet the ans... | What are the worst (commonly adopted) ideas/principles in statistics? | You have a nice answer to one that I posted a few weeks ago.
Debunking wrong CLT statement
False claim: the central limit theorem says that the empirical distribution converges to a normal distributio | What are the worst (commonly adopted) ideas/principles in statistics?
You have a nice answer to one that I posted a few weeks ago.
Debunking wrong CLT statement
False claim: the central limit theorem says that the empirical distribution converges to a normal distribution.
As the answers to my question show, that claim ... | What are the worst (commonly adopted) ideas/principles in statistics?
You have a nice answer to one that I posted a few weeks ago.
Debunking wrong CLT statement
False claim: the central limit theorem says that the empirical distribution converges to a normal distributio |
3,227 | What are the worst (commonly adopted) ideas/principles in statistics? | Equating a high $R^2$ with a "good model" (or equivalently, lamenting - or, in the case of referees of papers, criticizing - that $R^2$ is "too" low). More discussion is provided, e.g. here and here.
As should be universally appreciated, $R^2$ increases (more precisely, never decreases, see here) in the number of regre... | What are the worst (commonly adopted) ideas/principles in statistics? | Equating a high $R^2$ with a "good model" (or equivalently, lamenting - or, in the case of referees of papers, criticizing - that $R^2$ is "too" low). More discussion is provided, e.g. here and here.
| What are the worst (commonly adopted) ideas/principles in statistics?
Equating a high $R^2$ with a "good model" (or equivalently, lamenting - or, in the case of referees of papers, criticizing - that $R^2$ is "too" low). More discussion is provided, e.g. here and here.
As should be universally appreciated, $R^2$ increa... | What are the worst (commonly adopted) ideas/principles in statistics?
Equating a high $R^2$ with a "good model" (or equivalently, lamenting - or, in the case of referees of papers, criticizing - that $R^2$ is "too" low). More discussion is provided, e.g. here and here.
|
3,228 | What are the worst (commonly adopted) ideas/principles in statistics? | ARIMA!!! - a marvel of theoretical rigor and mathematical elegance that is almost useless for any realistic business time series.
Ok, that is an exaggeration: ARIMA and similar models like GARCH are occasionally useful. But ARIMA is not nearly as general purpose a model as most people seem to think it is.
Most competen... | What are the worst (commonly adopted) ideas/principles in statistics? | ARIMA!!! - a marvel of theoretical rigor and mathematical elegance that is almost useless for any realistic business time series.
Ok, that is an exaggeration: ARIMA and similar models like GARCH are o | What are the worst (commonly adopted) ideas/principles in statistics?
ARIMA!!! - a marvel of theoretical rigor and mathematical elegance that is almost useless for any realistic business time series.
Ok, that is an exaggeration: ARIMA and similar models like GARCH are occasionally useful. But ARIMA is not nearly as gen... | What are the worst (commonly adopted) ideas/principles in statistics?
ARIMA!!! - a marvel of theoretical rigor and mathematical elegance that is almost useless for any realistic business time series.
Ok, that is an exaggeration: ARIMA and similar models like GARCH are o |
3,229 | What are the worst (commonly adopted) ideas/principles in statistics? | Forgetting that bootstrapping requires special care when examining distributions of non-pivotal quantities (e.g., for estimating their confidence intervals), even though that has been known since the beginning. | What are the worst (commonly adopted) ideas/principles in statistics? | Forgetting that bootstrapping requires special care when examining distributions of non-pivotal quantities (e.g., for estimating their confidence intervals), even though that has been known since the | What are the worst (commonly adopted) ideas/principles in statistics?
Forgetting that bootstrapping requires special care when examining distributions of non-pivotal quantities (e.g., for estimating their confidence intervals), even though that has been known since the beginning. | What are the worst (commonly adopted) ideas/principles in statistics?
Forgetting that bootstrapping requires special care when examining distributions of non-pivotal quantities (e.g., for estimating their confidence intervals), even though that has been known since the |
3,230 | What are the worst (commonly adopted) ideas/principles in statistics? | "A complex model is better than a simple one". Or a variation thereof: "We need a model that can model nonlinearities."
Especially often heard in forecasting. There is a strong preconception that a more complex model will forecast better than a simple one.
That is very often not the case. | What are the worst (commonly adopted) ideas/principles in statistics? | "A complex model is better than a simple one". Or a variation thereof: "We need a model that can model nonlinearities."
Especially often heard in forecasting. There is a strong preconception that a mo | What are the worst (commonly adopted) ideas/principles in statistics?
"A complex model is better than a simple one". Or a variation thereof: "We need a model that can model nonlinearities."
Especially often heard in forecasting. There is a strong preconception that a more complex model will forecast better than a simpl... | What are the worst (commonly adopted) ideas/principles in statistics?
"A complex model is better than a simple one". Or a variation thereof: "We need a model that can model nonlinearities."
Especially often heard in forecasting. There is a strong preconception that a mo |
3,231 | What are the worst (commonly adopted) ideas/principles in statistics? | Doing statistical inference with a - most certainly - biased convenience sample. (And then caring primarily about normality instead of addressing bias...) | What are the worst (commonly adopted) ideas/principles in statistics? | Doing statistical inference with a - most certainly - biased convenience sample. (And then caring primarily about normality instead of addressing bias...) | What are the worst (commonly adopted) ideas/principles in statistics?
Doing statistical inference with a - most certainly - biased convenience sample. (And then caring primarily about normality instead of addressing bias...) | What are the worst (commonly adopted) ideas/principles in statistics?
Doing statistical inference with a - most certainly - biased convenience sample. (And then caring primarily about normality instead of addressing bias...) |
3,232 | What are the worst (commonly adopted) ideas/principles in statistics? | Assuming that controlling for covariates is equivalent to eliminating their causal impact—this is false.
The original example given by Pearl is that of qualifications, gender, and hiring. We hope that qualifications affect hiring, and want to know if gender does too. Gender can affect qualifications (unequal opportun... | What are the worst (commonly adopted) ideas/principles in statistics? | Assuming that controlling for covariates is equivalent to eliminating their causal impact—this is false.
The original example given by Pearl is that of qualifications, gender, and hiring. We hope tha | What are the worst (commonly adopted) ideas/principles in statistics?
Assuming that controlling for covariates is equivalent to eliminating their causal impact—this is false.
The original example given by Pearl is that of qualifications, gender, and hiring. We hope that qualifications affect hiring, and want to know i... | What are the worst (commonly adopted) ideas/principles in statistics?
Assuming that controlling for covariates is equivalent to eliminating their causal impact—this is false.
The original example given by Pearl is that of qualifications, gender, and hiring. We hope tha |
3,233 | What are the worst (commonly adopted) ideas/principles in statistics? | What does a p-value mean?
ALERT TO NEWCOMERS: THIS QUOTE IS EXTREMELY FALSE
“The probability that the null hypothesis is true, duh! Come on, Dave, you’re a professional statistician, and that’s Statistics 101.”
I get the appeal of this one, and it would be really nice to have a simple measure of the probability of the ... | What are the worst (commonly adopted) ideas/principles in statistics? | What does a p-value mean?
ALERT TO NEWCOMERS: THIS QUOTE IS EXTREMELY FALSE
“The probability that the null hypothesis is true, duh! Come on, Dave, you’re a professional statistician, and that’s Statis | What are the worst (commonly adopted) ideas/principles in statistics?
What does a p-value mean?
ALERT TO NEWCOMERS: THIS QUOTE IS EXTREMELY FALSE
“The probability that the null hypothesis is true, duh! Come on, Dave, you’re a professional statistician, and that’s Statistics 101.”
I get the appeal of this one, and it wo... | What are the worst (commonly adopted) ideas/principles in statistics?
What does a p-value mean?
ALERT TO NEWCOMERS: THIS QUOTE IS EXTREMELY FALSE
“The probability that the null hypothesis is true, duh! Come on, Dave, you’re a professional statistician, and that’s Statis |
3,234 | What are the worst (commonly adopted) ideas/principles in statistics? | It's not purely statistics, but more statistical modeling in the large sense, but a very common misconception, that I have also heard in some University courses, is that Random Forests cannot overfit.
Here
is a question where they asked exactly this, and I tried explaining why this isn't true, and where this misconcep... | What are the worst (commonly adopted) ideas/principles in statistics? | It's not purely statistics, but more statistical modeling in the large sense, but a very common misconception, that I have also heard in some University courses, is that Random Forests cannot overfit. | What are the worst (commonly adopted) ideas/principles in statistics?
It's not purely statistics, but more statistical modeling in the large sense, but a very common misconception, that I have also heard in some University courses, is that Random Forests cannot overfit.
Here
is a question where they asked exactly this... | What are the worst (commonly adopted) ideas/principles in statistics?
It's not purely statistics, but more statistical modeling in the large sense, but a very common misconception, that I have also heard in some University courses, is that Random Forests cannot overfit. |
3,235 | What are the worst (commonly adopted) ideas/principles in statistics? | People often assume that the uniform prior is uninformative. This is usually false. | What are the worst (commonly adopted) ideas/principles in statistics? | People often assume that the uniform prior is uninformative. This is usually false. | What are the worst (commonly adopted) ideas/principles in statistics?
People often assume that the uniform prior is uninformative. This is usually false. | What are the worst (commonly adopted) ideas/principles in statistics?
People often assume that the uniform prior is uninformative. This is usually false. |
3,236 | What are the worst (commonly adopted) ideas/principles in statistics? | In the medical community especially, and somewhat less often in psychology, the "change from baseline" is usually analyzed by modelling the change as a function of covariates. Doug Altman and Martin Bland have a really great paper on why this is probably not a good idea and argue that an ANVOCA (post measure ~ covaria... | What are the worst (commonly adopted) ideas/principles in statistics? | In the medical community especially, and somewhat less often in psychology, the "change from baseline" is usually analyzed by modelling the change as a function of covariates. Doug Altman and Martin | What are the worst (commonly adopted) ideas/principles in statistics?
In the medical community especially, and somewhat less often in psychology, the "change from baseline" is usually analyzed by modelling the change as a function of covariates. Doug Altman and Martin Bland have a really great paper on why this is pro... | What are the worst (commonly adopted) ideas/principles in statistics?
In the medical community especially, and somewhat less often in psychology, the "change from baseline" is usually analyzed by modelling the change as a function of covariates. Doug Altman and Martin |
3,237 | What are the worst (commonly adopted) ideas/principles in statistics? | Not realizing to what extent functional form assumptions and parametrizations are buying information in your analysis. In economics, you get these models that seem really interesting and give you a new way to potentially identify some effect of interest, but sometimes you read them and realize that without that last no... | What are the worst (commonly adopted) ideas/principles in statistics? | Not realizing to what extent functional form assumptions and parametrizations are buying information in your analysis. In economics, you get these models that seem really interesting and give you a ne | What are the worst (commonly adopted) ideas/principles in statistics?
Not realizing to what extent functional form assumptions and parametrizations are buying information in your analysis. In economics, you get these models that seem really interesting and give you a new way to potentially identify some effect of inter... | What are the worst (commonly adopted) ideas/principles in statistics?
Not realizing to what extent functional form assumptions and parametrizations are buying information in your analysis. In economics, you get these models that seem really interesting and give you a ne |
3,238 | What are the worst (commonly adopted) ideas/principles in statistics? | When analysing change, that it is OK to create change scores (followup - baseline or a percent change from baseline) and then regress them on baseline. It's not (mathematical coupling). ANCOVA is often suggested as the best approach and it might be in the case of randomisation to groups, such as in clinical trials, but... | What are the worst (commonly adopted) ideas/principles in statistics? | When analysing change, that it is OK to create change scores (followup - baseline or a percent change from baseline) and then regress them on baseline. It's not (mathematical coupling). ANCOVA is ofte | What are the worst (commonly adopted) ideas/principles in statistics?
When analysing change, that it is OK to create change scores (followup - baseline or a percent change from baseline) and then regress them on baseline. It's not (mathematical coupling). ANCOVA is often suggested as the best approach and it might be i... | What are the worst (commonly adopted) ideas/principles in statistics?
When analysing change, that it is OK to create change scores (followup - baseline or a percent change from baseline) and then regress them on baseline. It's not (mathematical coupling). ANCOVA is ofte |
3,239 | What are the worst (commonly adopted) ideas/principles in statistics? | Using interaction (product) terms in regressions without using curvilinear (quadratic) terms.
A few years ago I've been thinking about it (after seeing a few papers (in economic/management fields) that were doing it), and I realized that if in the true model the outcome variable depends on the square of some or all the... | What are the worst (commonly adopted) ideas/principles in statistics? | Using interaction (product) terms in regressions without using curvilinear (quadratic) terms.
A few years ago I've been thinking about it (after seeing a few papers (in economic/management fields) tha | What are the worst (commonly adopted) ideas/principles in statistics?
Using interaction (product) terms in regressions without using curvilinear (quadratic) terms.
A few years ago I've been thinking about it (after seeing a few papers (in economic/management fields) that were doing it), and I realized that if in the tr... | What are the worst (commonly adopted) ideas/principles in statistics?
Using interaction (product) terms in regressions without using curvilinear (quadratic) terms.
A few years ago I've been thinking about it (after seeing a few papers (in economic/management fields) tha |
3,240 | What are the worst (commonly adopted) ideas/principles in statistics? | I vote for "specification tests," e.g., White's test for heteroscedasticity, Hausman's tests, etc. These are common in econometrics and elsewhere, to the point where many people think they comprise the actual definition of the assumptions tested rather than a means to evaluate them. You would think the recent ASA state... | What are the worst (commonly adopted) ideas/principles in statistics? | I vote for "specification tests," e.g., White's test for heteroscedasticity, Hausman's tests, etc. These are common in econometrics and elsewhere, to the point where many people think they comprise th | What are the worst (commonly adopted) ideas/principles in statistics?
I vote for "specification tests," e.g., White's test for heteroscedasticity, Hausman's tests, etc. These are common in econometrics and elsewhere, to the point where many people think they comprise the actual definition of the assumptions tested rath... | What are the worst (commonly adopted) ideas/principles in statistics?
I vote for "specification tests," e.g., White's test for heteroscedasticity, Hausman's tests, etc. These are common in econometrics and elsewhere, to the point where many people think they comprise th |
3,241 | What are the worst (commonly adopted) ideas/principles in statistics? | “Correlation does not imply causation.”
This is a true statement. Even if there is causation, it could be in the opposite direction of what is asserted.
What I have seen happen is that, when the correlation is inconvenient, people take this to mean that correlation precludes causation.
I don’t see professional statisti... | What are the worst (commonly adopted) ideas/principles in statistics? | “Correlation does not imply causation.”
This is a true statement. Even if there is causation, it could be in the opposite direction of what is asserted.
What I have seen happen is that, when the corre | What are the worst (commonly adopted) ideas/principles in statistics?
“Correlation does not imply causation.”
This is a true statement. Even if there is causation, it could be in the opposite direction of what is asserted.
What I have seen happen is that, when the correlation is inconvenient, people take this to mean t... | What are the worst (commonly adopted) ideas/principles in statistics?
“Correlation does not imply causation.”
This is a true statement. Even if there is causation, it could be in the opposite direction of what is asserted.
What I have seen happen is that, when the corre |
3,242 | What are the worst (commonly adopted) ideas/principles in statistics? | Using statistical significance (usually at $1\%$, $5\%$ or $10\%$) of explanatory variables / regressors as a criterion in model building for explanatory or predictive purposes.
In explanatory modelling, both subject-matter and statistical validity are needed; see e.g. the probabilistic reduction approach to model buil... | What are the worst (commonly adopted) ideas/principles in statistics? | Using statistical significance (usually at $1\%$, $5\%$ or $10\%$) of explanatory variables / regressors as a criterion in model building for explanatory or predictive purposes.
In explanatory modelli | What are the worst (commonly adopted) ideas/principles in statistics?
Using statistical significance (usually at $1\%$, $5\%$ or $10\%$) of explanatory variables / regressors as a criterion in model building for explanatory or predictive purposes.
In explanatory modelling, both subject-matter and statistical validity a... | What are the worst (commonly adopted) ideas/principles in statistics?
Using statistical significance (usually at $1\%$, $5\%$ or $10\%$) of explanatory variables / regressors as a criterion in model building for explanatory or predictive purposes.
In explanatory modelli |
3,243 | What are the worst (commonly adopted) ideas/principles in statistics? | The 'rule of thumb' that the standard deviation $S$ of a normal sample can be usefully approximated as sample range $D$
divided by $4$ (or $5$ or $6).$
The rule is typically "illustrated" by an example, contrived
so the 'rule' gives a reasonable answer. In fact, the appropriate divisor
depends crucially on sample size ... | What are the worst (commonly adopted) ideas/principles in statistics? | The 'rule of thumb' that the standard deviation $S$ of a normal sample can be usefully approximated as sample range $D$
divided by $4$ (or $5$ or $6).$
The rule is typically "illustrated" by an exampl | What are the worst (commonly adopted) ideas/principles in statistics?
The 'rule of thumb' that the standard deviation $S$ of a normal sample can be usefully approximated as sample range $D$
divided by $4$ (or $5$ or $6).$
The rule is typically "illustrated" by an example, contrived
so the 'rule' gives a reasonable answ... | What are the worst (commonly adopted) ideas/principles in statistics?
The 'rule of thumb' that the standard deviation $S$ of a normal sample can be usefully approximated as sample range $D$
divided by $4$ (or $5$ or $6).$
The rule is typically "illustrated" by an exampl |
3,244 | What are the worst (commonly adopted) ideas/principles in statistics? | The idea that because we have in mind an "average" result, that a sequence of data that is either below or above the average means that a particular result "is due".
The examples are things like rolling a die, where a large number of "no six" outcomes are observed - surely a six is due soon! | What are the worst (commonly adopted) ideas/principles in statistics? | The idea that because we have in mind an "average" result, that a sequence of data that is either below or above the average means that a particular result "is due".
The examples are things like rolli | What are the worst (commonly adopted) ideas/principles in statistics?
The idea that because we have in mind an "average" result, that a sequence of data that is either below or above the average means that a particular result "is due".
The examples are things like rolling a die, where a large number of "no six" outcome... | What are the worst (commonly adopted) ideas/principles in statistics?
The idea that because we have in mind an "average" result, that a sequence of data that is either below or above the average means that a particular result "is due".
The examples are things like rolli |
3,245 | What are the worst (commonly adopted) ideas/principles in statistics? | My favorite stats malpractice: permuting features instead of samples in a permutation test. In genomics, it's common to get a big list of differentially expressed, or differentially methylated, or differentially accessible genes (or similar). Often this is full of unfamiliar items, because nobody knows the literature o... | What are the worst (commonly adopted) ideas/principles in statistics? | My favorite stats malpractice: permuting features instead of samples in a permutation test. In genomics, it's common to get a big list of differentially expressed, or differentially methylated, or dif | What are the worst (commonly adopted) ideas/principles in statistics?
My favorite stats malpractice: permuting features instead of samples in a permutation test. In genomics, it's common to get a big list of differentially expressed, or differentially methylated, or differentially accessible genes (or similar). Often t... | What are the worst (commonly adopted) ideas/principles in statistics?
My favorite stats malpractice: permuting features instead of samples in a permutation test. In genomics, it's common to get a big list of differentially expressed, or differentially methylated, or dif |
3,246 | What are the worst (commonly adopted) ideas/principles in statistics? | Examining the t-test for each variable in a regression, but not the F-tests for multiple variables.
A common practice in many fields that apply statistics, is to use a regression with many covariates in order to determine the effect of the covariates on the outcome(s) of interest.
In these researches it is common to us... | What are the worst (commonly adopted) ideas/principles in statistics? | Examining the t-test for each variable in a regression, but not the F-tests for multiple variables.
A common practice in many fields that apply statistics, is to use a regression with many covariates | What are the worst (commonly adopted) ideas/principles in statistics?
Examining the t-test for each variable in a regression, but not the F-tests for multiple variables.
A common practice in many fields that apply statistics, is to use a regression with many covariates in order to determine the effect of the covariates... | What are the worst (commonly adopted) ideas/principles in statistics?
Examining the t-test for each variable in a regression, but not the F-tests for multiple variables.
A common practice in many fields that apply statistics, is to use a regression with many covariates |
3,247 | What are the worst (commonly adopted) ideas/principles in statistics? | Post-selection inference, i.e. model building and doing inference on the same data set where the inference does not account for the model building stage.
Either: Given a data set and no predetermined model, a model is built based on the patterns found in the data set.
Or: Given a data set and a model, the model is ofte... | What are the worst (commonly adopted) ideas/principles in statistics? | Post-selection inference, i.e. model building and doing inference on the same data set where the inference does not account for the model building stage.
Either: Given a data set and no predetermined | What are the worst (commonly adopted) ideas/principles in statistics?
Post-selection inference, i.e. model building and doing inference on the same data set where the inference does not account for the model building stage.
Either: Given a data set and no predetermined model, a model is built based on the patterns foun... | What are the worst (commonly adopted) ideas/principles in statistics?
Post-selection inference, i.e. model building and doing inference on the same data set where the inference does not account for the model building stage.
Either: Given a data set and no predetermined |
3,248 | What are the worst (commonly adopted) ideas/principles in statistics? | Calling type I assertion probability the "type I error rate" when it is neither a rate nor the probability of making an error. It is the probability of making an assertion of an effect when there is no effect.
Calling type I assertion probability the "false positive rate" when it is not the probability of a false posi... | What are the worst (commonly adopted) ideas/principles in statistics? | Calling type I assertion probability the "type I error rate" when it is neither a rate nor the probability of making an error. It is the probability of making an assertion of an effect when there is | What are the worst (commonly adopted) ideas/principles in statistics?
Calling type I assertion probability the "type I error rate" when it is neither a rate nor the probability of making an error. It is the probability of making an assertion of an effect when there is no effect.
Calling type I assertion probability th... | What are the worst (commonly adopted) ideas/principles in statistics?
Calling type I assertion probability the "type I error rate" when it is neither a rate nor the probability of making an error. It is the probability of making an assertion of an effect when there is |
3,249 | Statistics interview questions | Not sure what the job is, but I think "Explain x to a novice" would probably be good-
a) because they will probably need to do this in the job
b) it's a good test of understanding, I reckon. | Statistics interview questions | Not sure what the job is, but I think "Explain x to a novice" would probably be good-
a) because they will probably need to do this in the job
b) it's a good test of understanding, I reckon. | Statistics interview questions
Not sure what the job is, but I think "Explain x to a novice" would probably be good-
a) because they will probably need to do this in the job
b) it's a good test of understanding, I reckon. | Statistics interview questions
Not sure what the job is, but I think "Explain x to a novice" would probably be good-
a) because they will probably need to do this in the job
b) it's a good test of understanding, I reckon. |
3,250 | Statistics interview questions | Standard Q where I work is along the lines of:
Have a look at this output of a multiple logistic regression from a statistical package you claim to have used (preferably one we use too). XXX is the independent variable of principal interest. How woud you interpret the results for a colleague with knowledge of the subj... | Statistics interview questions | Standard Q where I work is along the lines of:
Have a look at this output of a multiple logistic regression from a statistical package you claim to have used (preferably one we use too). XXX is the i | Statistics interview questions
Standard Q where I work is along the lines of:
Have a look at this output of a multiple logistic regression from a statistical package you claim to have used (preferably one we use too). XXX is the independent variable of principal interest. How woud you interpret the results for a colle... | Statistics interview questions
Standard Q where I work is along the lines of:
Have a look at this output of a multiple logistic regression from a statistical package you claim to have used (preferably one we use too). XXX is the i |
3,251 | Statistics interview questions | You might also want to reflect on whether the interview is the best medium for measuring the construct of interest.
If you want to measure prior knowledge of probability or statistics, you might be better off relying more on a written test.
You can ask more questions, and thus increase reliability of measurement. It's ... | Statistics interview questions | You might also want to reflect on whether the interview is the best medium for measuring the construct of interest.
If you want to measure prior knowledge of probability or statistics, you might be be | Statistics interview questions
You might also want to reflect on whether the interview is the best medium for measuring the construct of interest.
If you want to measure prior knowledge of probability or statistics, you might be better off relying more on a written test.
You can ask more questions, and thus increase re... | Statistics interview questions
You might also want to reflect on whether the interview is the best medium for measuring the construct of interest.
If you want to measure prior knowledge of probability or statistics, you might be be |
3,252 | Statistics interview questions | Many questions/answers on this site could give ideas for good questions. I will give a list with some such links that I think are good. Posts where I answered are overrepresented, because I know those posts better, not because they necessarily are the best! I give short comments to each link, so you can decide if you... | Statistics interview questions | Many questions/answers on this site could give ideas for good questions. I will give a list with some such links that I think are good. Posts where I answered are overrepresented, because I know thos | Statistics interview questions
Many questions/answers on this site could give ideas for good questions. I will give a list with some such links that I think are good. Posts where I answered are overrepresented, because I know those posts better, not because they necessarily are the best! I give short comments to each... | Statistics interview questions
Many questions/answers on this site could give ideas for good questions. I will give a list with some such links that I think are good. Posts where I answered are overrepresented, because I know thos |
3,253 | Statistics interview questions | Two questions I've been asked:
1) You fit a multiple regression to examine the effect of a particular variable a worker in another department is interested in. The variable comes back insignificant, but your co-worker says that this is impossible as it is known to have an effect. What would you say/do?
2) You have ... | Statistics interview questions | Two questions I've been asked:
1) You fit a multiple regression to examine the effect of a particular variable a worker in another department is interested in. The variable comes back insignificant, | Statistics interview questions
Two questions I've been asked:
1) You fit a multiple regression to examine the effect of a particular variable a worker in another department is interested in. The variable comes back insignificant, but your co-worker says that this is impossible as it is known to have an effect. What ... | Statistics interview questions
Two questions I've been asked:
1) You fit a multiple regression to examine the effect of a particular variable a worker in another department is interested in. The variable comes back insignificant, |
3,254 | Statistics interview questions | Here is a big data set. What is your
plan for dealing with outliers? How
about missing values? How about transformations?
Can they deal with real-world data? | Statistics interview questions | Here is a big data set. What is your
plan for dealing with outliers? How
about missing values? How about transformations?
Can they deal with real-world data? | Statistics interview questions
Here is a big data set. What is your
plan for dealing with outliers? How
about missing values? How about transformations?
Can they deal with real-world data? | Statistics interview questions
Here is a big data set. What is your
plan for dealing with outliers? How
about missing values? How about transformations?
Can they deal with real-world data? |
3,255 | Statistics interview questions | I was asked once how I would explain the relevance of the central limit theorem to a class of freshmen in the social sciences that barely have knowledge about statistics. | Statistics interview questions | I was asked once how I would explain the relevance of the central limit theorem to a class of freshmen in the social sciences that barely have knowledge about statistics. | Statistics interview questions
I was asked once how I would explain the relevance of the central limit theorem to a class of freshmen in the social sciences that barely have knowledge about statistics. | Statistics interview questions
I was asked once how I would explain the relevance of the central limit theorem to a class of freshmen in the social sciences that barely have knowledge about statistics. |
3,256 | Statistics interview questions | How do you prevent over-fitting when
you are creating a statistical model?
Good answer: cross-validation | Statistics interview questions | How do you prevent over-fitting when
you are creating a statistical model?
Good answer: cross-validation | Statistics interview questions
How do you prevent over-fitting when
you are creating a statistical model?
Good answer: cross-validation | Statistics interview questions
How do you prevent over-fitting when
you are creating a statistical model?
Good answer: cross-validation |
3,257 | Statistics interview questions | How do you numericize something that
is not numerical?
Example, "Automatic Feature Extraction for Classifying Audio Data"
Rationale: Can they figure out how to analyze something statistically that is not already in a big table? | Statistics interview questions | How do you numericize something that
is not numerical?
Example, "Automatic Feature Extraction for Classifying Audio Data"
Rationale: Can they figure out how to analyze something statistically that is | Statistics interview questions
How do you numericize something that
is not numerical?
Example, "Automatic Feature Extraction for Classifying Audio Data"
Rationale: Can they figure out how to analyze something statistically that is not already in a big table? | Statistics interview questions
How do you numericize something that
is not numerical?
Example, "Automatic Feature Extraction for Classifying Audio Data"
Rationale: Can they figure out how to analyze something statistically that is |
3,258 | Statistics interview questions | I often ask "how would you define/explain what forecasting is?"
Answer to that type of very general question helps me to see if people are connected to a particular case of forecasting. There is not a right answer but answering this synthetically during an interview is not always easy:) | Statistics interview questions | I often ask "how would you define/explain what forecasting is?"
Answer to that type of very general question helps me to see if people are connected to a particular case of forecasting. There is not | Statistics interview questions
I often ask "how would you define/explain what forecasting is?"
Answer to that type of very general question helps me to see if people are connected to a particular case of forecasting. There is not a right answer but answering this synthetically during an interview is not always easy:) | Statistics interview questions
I often ask "how would you define/explain what forecasting is?"
Answer to that type of very general question helps me to see if people are connected to a particular case of forecasting. There is not |
3,259 | Statistics interview questions | For an observational data context:
Consider this regression model applied to this substantive problem. What, if anything, in it can be interpreted causally? [Further probe] What would you need to learn to change your opinion? | Statistics interview questions | For an observational data context:
Consider this regression model applied to this substantive problem. What, if anything, in it can be interpreted causally? [Further probe] What would you need to l | Statistics interview questions
For an observational data context:
Consider this regression model applied to this substantive problem. What, if anything, in it can be interpreted causally? [Further probe] What would you need to learn to change your opinion? | Statistics interview questions
For an observational data context:
Consider this regression model applied to this substantive problem. What, if anything, in it can be interpreted causally? [Further probe] What would you need to l |
3,260 | Statistics interview questions | How will you count the number of sandal wood trees in Bangalore ? | Statistics interview questions | How will you count the number of sandal wood trees in Bangalore ? | Statistics interview questions
How will you count the number of sandal wood trees in Bangalore ? | Statistics interview questions
How will you count the number of sandal wood trees in Bangalore ? |
3,261 | Statistics interview questions | Under the heading Causation vs correlation:
It's common to use customer/user engagement as features for a predictive model. For example, people who click on this button at more likely to subscribe than people who don't. People who shop on Mondays are more likely to shop again than those who shop on Tuesdays.
If we take... | Statistics interview questions | Under the heading Causation vs correlation:
It's common to use customer/user engagement as features for a predictive model. For example, people who click on this button at more likely to subscribe tha | Statistics interview questions
Under the heading Causation vs correlation:
It's common to use customer/user engagement as features for a predictive model. For example, people who click on this button at more likely to subscribe than people who don't. People who shop on Mondays are more likely to shop again than those w... | Statistics interview questions
Under the heading Causation vs correlation:
It's common to use customer/user engagement as features for a predictive model. For example, people who click on this button at more likely to subscribe tha |
3,262 | Statistics interview questions | A lot of the questions we ask are similar to those that have already been described. But some that I haven't read yet, that are used: you might be asked to sketch out a program on a whiteboard to do something like: simulate a dice rolling or other probability problem, or calculate a series of prime numbers (e.g. all t... | Statistics interview questions | A lot of the questions we ask are similar to those that have already been described. But some that I haven't read yet, that are used: you might be asked to sketch out a program on a whiteboard to do s | Statistics interview questions
A lot of the questions we ask are similar to those that have already been described. But some that I haven't read yet, that are used: you might be asked to sketch out a program on a whiteboard to do something like: simulate a dice rolling or other probability problem, or calculate a seri... | Statistics interview questions
A lot of the questions we ask are similar to those that have already been described. But some that I haven't read yet, that are used: you might be asked to sketch out a program on a whiteboard to do s |
3,263 | Statistics interview questions | Here is a TinkerToy set. Show me
how Euclidean distance works in three
dimensions. Now show me how multiple regression works.
Can they explain how statistics works in the physical world? | Statistics interview questions | Here is a TinkerToy set. Show me
how Euclidean distance works in three
dimensions. Now show me how multiple regression works.
Can they explain how statistics works in the physical world? | Statistics interview questions
Here is a TinkerToy set. Show me
how Euclidean distance works in three
dimensions. Now show me how multiple regression works.
Can they explain how statistics works in the physical world? | Statistics interview questions
Here is a TinkerToy set. Show me
how Euclidean distance works in three
dimensions. Now show me how multiple regression works.
Can they explain how statistics works in the physical world? |
3,264 | Statistics interview questions | We are running a customer service centre. We are getting 1 million calls per month. How do we reduce it to ten thousand ? | Statistics interview questions | We are running a customer service centre. We are getting 1 million calls per month. How do we reduce it to ten thousand ? | Statistics interview questions
We are running a customer service centre. We are getting 1 million calls per month. How do we reduce it to ten thousand ? | Statistics interview questions
We are running a customer service centre. We are getting 1 million calls per month. How do we reduce it to ten thousand ? |
3,265 | Statistics interview questions | While doing the variance analysis of quantitative variable, sometimes it found that frequency of the variable are very high (>5) then we use the Fisher's exact test to find independence of the variable. | Statistics interview questions | While doing the variance analysis of quantitative variable, sometimes it found that frequency of the variable are very high (>5) then we use the Fisher's exact test to find independence of the variabl | Statistics interview questions
While doing the variance analysis of quantitative variable, sometimes it found that frequency of the variable are very high (>5) then we use the Fisher's exact test to find independence of the variable. | Statistics interview questions
While doing the variance analysis of quantitative variable, sometimes it found that frequency of the variable are very high (>5) then we use the Fisher's exact test to find independence of the variabl |
3,266 | Statistics interview questions | The average paid attendance at Yankees games last year was 55,000. You randomly ask a bunch of people in NYC if they went to a Yankees game last season, and if they did, you record the paid attendance. What is the average paid attendance for the games that the people you asked who went to a game attended?
I'll give y... | Statistics interview questions | The average paid attendance at Yankees games last year was 55,000. You randomly ask a bunch of people in NYC if they went to a Yankees game last season, and if they did, you record the paid attendanc | Statistics interview questions
The average paid attendance at Yankees games last year was 55,000. You randomly ask a bunch of people in NYC if they went to a Yankees game last season, and if they did, you record the paid attendance. What is the average paid attendance for the games that the people you asked who went ... | Statistics interview questions
The average paid attendance at Yankees games last year was 55,000. You randomly ask a bunch of people in NYC if they went to a Yankees game last season, and if they did, you record the paid attendanc |
3,267 | What is so cool about de Finetti's representation theorem? | De Finetti's Representation Theorem gives in a single take, within the subjectivistic interpretation of probabilities, the raison d'être of statistical models and the meaning of parameters and their prior distributions.
Suppose that the random variables $X_1,\dots,X_n$ represent the results of successive tosses of a c... | What is so cool about de Finetti's representation theorem? | De Finetti's Representation Theorem gives in a single take, within the subjectivistic interpretation of probabilities, the raison d'être of statistical models and the meaning of parameters and their p | What is so cool about de Finetti's representation theorem?
De Finetti's Representation Theorem gives in a single take, within the subjectivistic interpretation of probabilities, the raison d'être of statistical models and the meaning of parameters and their prior distributions.
Suppose that the random variables $X_1,\... | What is so cool about de Finetti's representation theorem?
De Finetti's Representation Theorem gives in a single take, within the subjectivistic interpretation of probabilities, the raison d'être of statistical models and the meaning of parameters and their p |
3,268 | What is so cool about de Finetti's representation theorem? | Everything is mathematically correct in Zen's answer. However I disagree on some points. Please be aware that I don't claim/believe my point of view is the good one; on the contrary I feel these points are not entirely clear for me yet. These are somewhat philosophical questions about which I like to discuss (and a goo... | What is so cool about de Finetti's representation theorem? | Everything is mathematically correct in Zen's answer. However I disagree on some points. Please be aware that I don't claim/believe my point of view is the good one; on the contrary I feel these point | What is so cool about de Finetti's representation theorem?
Everything is mathematically correct in Zen's answer. However I disagree on some points. Please be aware that I don't claim/believe my point of view is the good one; on the contrary I feel these points are not entirely clear for me yet. These are somewhat philo... | What is so cool about de Finetti's representation theorem?
Everything is mathematically correct in Zen's answer. However I disagree on some points. Please be aware that I don't claim/believe my point of view is the good one; on the contrary I feel these point |
3,269 | What is so cool about de Finetti's representation theorem? | You guys might be interested in a paper on this subject (journal subscription required for access - try accessing it from your university):
O'Neill, B. (2011) Exchangeability, correlation and Bayes' Effect. International Statistical Review 77(2), pp. 241-250.
This paper discusses the representation theorem as the basis... | What is so cool about de Finetti's representation theorem? | You guys might be interested in a paper on this subject (journal subscription required for access - try accessing it from your university):
O'Neill, B. (2011) Exchangeability, correlation and Bayes' E | What is so cool about de Finetti's representation theorem?
You guys might be interested in a paper on this subject (journal subscription required for access - try accessing it from your university):
O'Neill, B. (2011) Exchangeability, correlation and Bayes' Effect. International Statistical Review 77(2), pp. 241-250.
T... | What is so cool about de Finetti's representation theorem?
You guys might be interested in a paper on this subject (journal subscription required for access - try accessing it from your university):
O'Neill, B. (2011) Exchangeability, correlation and Bayes' E |
3,270 | What is so cool about de Finetti's representation theorem? | I'll try to counter the assertion that the theorem isn't directly useful, with a topical example: COVID modeling.
I think we're seen that models that try to replicate reality in all its detail have proven hard to steer during this crisis, leading to poor predictions despite noble and urgent efforts to recalibrate them.... | What is so cool about de Finetti's representation theorem? | I'll try to counter the assertion that the theorem isn't directly useful, with a topical example: COVID modeling.
I think we're seen that models that try to replicate reality in all its detail have pr | What is so cool about de Finetti's representation theorem?
I'll try to counter the assertion that the theorem isn't directly useful, with a topical example: COVID modeling.
I think we're seen that models that try to replicate reality in all its detail have proven hard to steer during this crisis, leading to poor predic... | What is so cool about de Finetti's representation theorem?
I'll try to counter the assertion that the theorem isn't directly useful, with a topical example: COVID modeling.
I think we're seen that models that try to replicate reality in all its detail have pr |
3,271 | Are there cases where PCA is more suitable than t-SNE? | $t$-SNE is a great piece of Machine Learning but one can find many reasons to use PCA instead of it. Of the top of my head, I will mention five. As most other computational methodologies in use, $t$-SNE is no silver bullet and there are quite a few reasons that make it a suboptimal choice in some cases. Let me mention ... | Are there cases where PCA is more suitable than t-SNE? | $t$-SNE is a great piece of Machine Learning but one can find many reasons to use PCA instead of it. Of the top of my head, I will mention five. As most other computational methodologies in use, $t$-S | Are there cases where PCA is more suitable than t-SNE?
$t$-SNE is a great piece of Machine Learning but one can find many reasons to use PCA instead of it. Of the top of my head, I will mention five. As most other computational methodologies in use, $t$-SNE is no silver bullet and there are quite a few reasons that mak... | Are there cases where PCA is more suitable than t-SNE?
$t$-SNE is a great piece of Machine Learning but one can find many reasons to use PCA instead of it. Of the top of my head, I will mention five. As most other computational methodologies in use, $t$-S |
3,272 | Are there cases where PCA is more suitable than t-SNE? | https://stats.stackexchange.com/a/249520/7828
is an excellent general answer.
I'd like to focus a bit more on your problem. You apparently want to see how your samples relate with respect to your 7 input variables. That is something t-SNE doesn't do. The idea of SNE and t-SNE is to place neighbors close to each other, ... | Are there cases where PCA is more suitable than t-SNE? | https://stats.stackexchange.com/a/249520/7828
is an excellent general answer.
I'd like to focus a bit more on your problem. You apparently want to see how your samples relate with respect to your 7 in | Are there cases where PCA is more suitable than t-SNE?
https://stats.stackexchange.com/a/249520/7828
is an excellent general answer.
I'd like to focus a bit more on your problem. You apparently want to see how your samples relate with respect to your 7 input variables. That is something t-SNE doesn't do. The idea of SN... | Are there cases where PCA is more suitable than t-SNE?
https://stats.stackexchange.com/a/249520/7828
is an excellent general answer.
I'd like to focus a bit more on your problem. You apparently want to see how your samples relate with respect to your 7 in |
3,273 | Are there cases where PCA is more suitable than t-SNE? | There are many very good points which have been given already here. However, there are some that I would like to stress. One is that PCA will preserves things that tSNE will not. This may be good or bad, depending on what you are trying to achieve. Per example tSNE will not preserve cluster sizes, while PCA will (see t... | Are there cases where PCA is more suitable than t-SNE? | There are many very good points which have been given already here. However, there are some that I would like to stress. One is that PCA will preserves things that tSNE will not. This may be good or b | Are there cases where PCA is more suitable than t-SNE?
There are many very good points which have been given already here. However, there are some that I would like to stress. One is that PCA will preserves things that tSNE will not. This may be good or bad, depending on what you are trying to achieve. Per example tSNE... | Are there cases where PCA is more suitable than t-SNE?
There are many very good points which have been given already here. However, there are some that I would like to stress. One is that PCA will preserves things that tSNE will not. This may be good or b |
3,274 | Are there cases where PCA is more suitable than t-SNE? | To give one applied angle, PCA and t-SNE are not mutually exclusive. In some fields of biology we are dealing with highly dimensional data where t-SNE simply does not scale. Therefore, we use PCA first to reduce the dimensionality of the data and then, taking the top principle components, we apply t-SNE (or a similar n... | Are there cases where PCA is more suitable than t-SNE? | To give one applied angle, PCA and t-SNE are not mutually exclusive. In some fields of biology we are dealing with highly dimensional data where t-SNE simply does not scale. Therefore, we use PCA firs | Are there cases where PCA is more suitable than t-SNE?
To give one applied angle, PCA and t-SNE are not mutually exclusive. In some fields of biology we are dealing with highly dimensional data where t-SNE simply does not scale. Therefore, we use PCA first to reduce the dimensionality of the data and then, taking the t... | Are there cases where PCA is more suitable than t-SNE?
To give one applied angle, PCA and t-SNE are not mutually exclusive. In some fields of biology we are dealing with highly dimensional data where t-SNE simply does not scale. Therefore, we use PCA firs |
3,275 | Does it make sense to add a quadratic term but not the linear term to a model? | 1. Why include the linear term?
It is illuminating to notice that a quadratic relationship can be written in two ways:
$$y = a_0 + a_1 x + a_2 x^2 = a_2(x - b)^2 + c$$
(where, equating coefficients, we find $-2a_2 b = a_1$ and $a_2 b^2 + c = a_0$). The value $x=b$ corresponds to a global extremum of the relationship (... | Does it make sense to add a quadratic term but not the linear term to a model? | 1. Why include the linear term?
It is illuminating to notice that a quadratic relationship can be written in two ways:
$$y = a_0 + a_1 x + a_2 x^2 = a_2(x - b)^2 + c$$
(where, equating coefficients, w | Does it make sense to add a quadratic term but not the linear term to a model?
1. Why include the linear term?
It is illuminating to notice that a quadratic relationship can be written in two ways:
$$y = a_0 + a_1 x + a_2 x^2 = a_2(x - b)^2 + c$$
(where, equating coefficients, we find $-2a_2 b = a_1$ and $a_2 b^2 + c =... | Does it make sense to add a quadratic term but not the linear term to a model?
1. Why include the linear term?
It is illuminating to notice that a quadratic relationship can be written in two ways:
$$y = a_0 + a_1 x + a_2 x^2 = a_2(x - b)^2 + c$$
(where, equating coefficients, w |
3,276 | Does it make sense to add a quadratic term but not the linear term to a model? | @whuber has given a really excellent answer here. I just want to add a small complimentary point. The question states that "a linear relation of predictor and data is not interpretable". This hints at a common misunderstanding, although I usually hear it on the other end ('what is the interpretation of the squared [... | Does it make sense to add a quadratic term but not the linear term to a model? | @whuber has given a really excellent answer here. I just want to add a small complimentary point. The question states that "a linear relation of predictor and data is not interpretable". This hints | Does it make sense to add a quadratic term but not the linear term to a model?
@whuber has given a really excellent answer here. I just want to add a small complimentary point. The question states that "a linear relation of predictor and data is not interpretable". This hints at a common misunderstanding, although I... | Does it make sense to add a quadratic term but not the linear term to a model?
@whuber has given a really excellent answer here. I just want to add a small complimentary point. The question states that "a linear relation of predictor and data is not interpretable". This hints |
3,277 | Does it make sense to add a quadratic term but not the linear term to a model? | @whuber's answer above is right on target in pointing out that omitting the linear term is the "usual" quadratic model is equivalent to saying, "I am absolutely certain that the extremum is at $x=0$."
However, you also need to check whether the software you are using has a "gotcha". Some software may automatically cen... | Does it make sense to add a quadratic term but not the linear term to a model? | @whuber's answer above is right on target in pointing out that omitting the linear term is the "usual" quadratic model is equivalent to saying, "I am absolutely certain that the extremum is at $x=0$." | Does it make sense to add a quadratic term but not the linear term to a model?
@whuber's answer above is right on target in pointing out that omitting the linear term is the "usual" quadratic model is equivalent to saying, "I am absolutely certain that the extremum is at $x=0$."
However, you also need to check whether ... | Does it make sense to add a quadratic term but not the linear term to a model?
@whuber's answer above is right on target in pointing out that omitting the linear term is the "usual" quadratic model is equivalent to saying, "I am absolutely certain that the extremum is at $x=0$." |
3,278 | Does it make sense to add a quadratic term but not the linear term to a model? | Brambor, Clark and Golder (2006) (which comes with an internet appendix) have a very clear take on how to understand interaction models and how to avoid the common pitfalls, including why you should (almost) always include the lower-order terms ("constitutive terms") in interaction models.
Analysts should include all ... | Does it make sense to add a quadratic term but not the linear term to a model? | Brambor, Clark and Golder (2006) (which comes with an internet appendix) have a very clear take on how to understand interaction models and how to avoid the common pitfalls, including why you should ( | Does it make sense to add a quadratic term but not the linear term to a model?
Brambor, Clark and Golder (2006) (which comes with an internet appendix) have a very clear take on how to understand interaction models and how to avoid the common pitfalls, including why you should (almost) always include the lower-order te... | Does it make sense to add a quadratic term but not the linear term to a model?
Brambor, Clark and Golder (2006) (which comes with an internet appendix) have a very clear take on how to understand interaction models and how to avoid the common pitfalls, including why you should ( |
3,279 | What are good basic statistics to use for ordinal data? | A frequency table is a good place to start. You can do the count, and relative frequency for each level. Also, the total count, and number of missing values may be of use.
You can also use a contingency table to compare two variables at once. Can display using a mosaic plot too. | What are good basic statistics to use for ordinal data? | A frequency table is a good place to start. You can do the count, and relative frequency for each level. Also, the total count, and number of missing values may be of use.
You can also use a continge | What are good basic statistics to use for ordinal data?
A frequency table is a good place to start. You can do the count, and relative frequency for each level. Also, the total count, and number of missing values may be of use.
You can also use a contingency table to compare two variables at once. Can display using a ... | What are good basic statistics to use for ordinal data?
A frequency table is a good place to start. You can do the count, and relative frequency for each level. Also, the total count, and number of missing values may be of use.
You can also use a continge |
3,280 | What are good basic statistics to use for ordinal data? | I'm going to argue from an applied perspective that the mean is often the best choice for summarising the central tendency of a Likert item.
Specifically, I'm thinking of contexts such as student satisfaction surveys, market research scales, employee opinion surveys, personality test items, and many social science surv... | What are good basic statistics to use for ordinal data? | I'm going to argue from an applied perspective that the mean is often the best choice for summarising the central tendency of a Likert item.
Specifically, I'm thinking of contexts such as student sati | What are good basic statistics to use for ordinal data?
I'm going to argue from an applied perspective that the mean is often the best choice for summarising the central tendency of a Likert item.
Specifically, I'm thinking of contexts such as student satisfaction surveys, market research scales, employee opinion surve... | What are good basic statistics to use for ordinal data?
I'm going to argue from an applied perspective that the mean is often the best choice for summarising the central tendency of a Likert item.
Specifically, I'm thinking of contexts such as student sati |
3,281 | What are good basic statistics to use for ordinal data? | For basic summaries, I agree that reporting frequency tables and some indication about central tendency is fine. For inference, a recent article published in PARE discussed t- vs. MWW-test, Five-Point Likert Items: t test versus Mann-Whitney-Wilcoxon.
For more elaborated treatment, I would recommend reading Agresti's r... | What are good basic statistics to use for ordinal data? | For basic summaries, I agree that reporting frequency tables and some indication about central tendency is fine. For inference, a recent article published in PARE discussed t- vs. MWW-test, Five-Point | What are good basic statistics to use for ordinal data?
For basic summaries, I agree that reporting frequency tables and some indication about central tendency is fine. For inference, a recent article published in PARE discussed t- vs. MWW-test, Five-Point Likert Items: t test versus Mann-Whitney-Wilcoxon.
For more ela... | What are good basic statistics to use for ordinal data?
For basic summaries, I agree that reporting frequency tables and some indication about central tendency is fine. For inference, a recent article published in PARE discussed t- vs. MWW-test, Five-Point |
3,282 | What are good basic statistics to use for ordinal data? | Conventional practice is to use the non-parametric statistics rank sum and mean rank to describe ordinal data.
Here's how they work:
Rank Sum
assign a rank to each member in each
group;
e.g., suppose you are looking at goals for each
player on two opposing football
teams then rank each member on
both teams from first ... | What are good basic statistics to use for ordinal data? | Conventional practice is to use the non-parametric statistics rank sum and mean rank to describe ordinal data.
Here's how they work:
Rank Sum
assign a rank to each member in each
group;
e.g., suppose | What are good basic statistics to use for ordinal data?
Conventional practice is to use the non-parametric statistics rank sum and mean rank to describe ordinal data.
Here's how they work:
Rank Sum
assign a rank to each member in each
group;
e.g., suppose you are looking at goals for each
player on two opposing footba... | What are good basic statistics to use for ordinal data?
Conventional practice is to use the non-parametric statistics rank sum and mean rank to describe ordinal data.
Here's how they work:
Rank Sum
assign a rank to each member in each
group;
e.g., suppose |
3,283 | What are good basic statistics to use for ordinal data? | Based on the abstract This article may be helpful for comparing several variables that are Likert scale. It compares two types of non-parametric multiple comparison tests: One based on ranks and one based on a test by Chacko. It includes simulations. | What are good basic statistics to use for ordinal data? | Based on the abstract This article may be helpful for comparing several variables that are Likert scale. It compares two types of non-parametric multiple comparison tests: One based on ranks and one b | What are good basic statistics to use for ordinal data?
Based on the abstract This article may be helpful for comparing several variables that are Likert scale. It compares two types of non-parametric multiple comparison tests: One based on ranks and one based on a test by Chacko. It includes simulations. | What are good basic statistics to use for ordinal data?
Based on the abstract This article may be helpful for comparing several variables that are Likert scale. It compares two types of non-parametric multiple comparison tests: One based on ranks and one b |
3,284 | What are good basic statistics to use for ordinal data? | I usually like to use Mosaic plot. You can create them by incoorporating other covariates of interest (such as: sex, stratified factors etc.) | What are good basic statistics to use for ordinal data? | I usually like to use Mosaic plot. You can create them by incoorporating other covariates of interest (such as: sex, stratified factors etc.) | What are good basic statistics to use for ordinal data?
I usually like to use Mosaic plot. You can create them by incoorporating other covariates of interest (such as: sex, stratified factors etc.) | What are good basic statistics to use for ordinal data?
I usually like to use Mosaic plot. You can create them by incoorporating other covariates of interest (such as: sex, stratified factors etc.) |
3,285 | What are good basic statistics to use for ordinal data? | I agree with Jeromy Anglim's evaluation. Remember that Likert responses are estimates — you are not using a perfectly reliable ruler to measure a physical object with stable dimensions. The mean is a powerful measure when using reasonable sample sizes.
In business and product R&D, the mean is by far the most common sta... | What are good basic statistics to use for ordinal data? | I agree with Jeromy Anglim's evaluation. Remember that Likert responses are estimates — you are not using a perfectly reliable ruler to measure a physical object with stable dimensions. The mean is a | What are good basic statistics to use for ordinal data?
I agree with Jeromy Anglim's evaluation. Remember that Likert responses are estimates — you are not using a perfectly reliable ruler to measure a physical object with stable dimensions. The mean is a powerful measure when using reasonable sample sizes.
In business... | What are good basic statistics to use for ordinal data?
I agree with Jeromy Anglim's evaluation. Remember that Likert responses are estimates — you are not using a perfectly reliable ruler to measure a physical object with stable dimensions. The mean is a |
3,286 | What are good basic statistics to use for ordinal data? | "Box scores" are often used to summarize ordinal data, particularly when it comes with meaningful verbal anchors. In other words, you might report "top 2 box", the percentage that chose either "agree" or "strongly agree". | What are good basic statistics to use for ordinal data? | "Box scores" are often used to summarize ordinal data, particularly when it comes with meaningful verbal anchors. In other words, you might report "top 2 box", the percentage that chose either "agree | What are good basic statistics to use for ordinal data?
"Box scores" are often used to summarize ordinal data, particularly when it comes with meaningful verbal anchors. In other words, you might report "top 2 box", the percentage that chose either "agree" or "strongly agree". | What are good basic statistics to use for ordinal data?
"Box scores" are often used to summarize ordinal data, particularly when it comes with meaningful verbal anchors. In other words, you might report "top 2 box", the percentage that chose either "agree |
3,287 | When are Log scales appropriate? | This is a very interesting question, and one that too few people think about. There are several different ways that a log scale can be appropriate. The first and most well known is that mentioned by Macro in his comment: log scales allow a large range to be displayed without small values being compressed down into bott... | When are Log scales appropriate? | This is a very interesting question, and one that too few people think about. There are several different ways that a log scale can be appropriate. The first and most well known is that mentioned by M | When are Log scales appropriate?
This is a very interesting question, and one that too few people think about. There are several different ways that a log scale can be appropriate. The first and most well known is that mentioned by Macro in his comment: log scales allow a large range to be displayed without small value... | When are Log scales appropriate?
This is a very interesting question, and one that too few people think about. There are several different ways that a log scale can be appropriate. The first and most well known is that mentioned by M |
3,288 | When are Log scales appropriate? | Some real life examples I had to hand as an addition to @Michael Lew's very good answer.
First, the two time series plots below show monthly visitor arrivals to New Zealand, available from Statistics New Zealand. Both plots have their purpose, but I find the one with the vertical axis on a logarithmic scale spectacula... | When are Log scales appropriate? | Some real life examples I had to hand as an addition to @Michael Lew's very good answer.
First, the two time series plots below show monthly visitor arrivals to New Zealand, available from Statistics | When are Log scales appropriate?
Some real life examples I had to hand as an addition to @Michael Lew's very good answer.
First, the two time series plots below show monthly visitor arrivals to New Zealand, available from Statistics New Zealand. Both plots have their purpose, but I find the one with the vertical axis ... | When are Log scales appropriate?
Some real life examples I had to hand as an addition to @Michael Lew's very good answer.
First, the two time series plots below show monthly visitor arrivals to New Zealand, available from Statistics |
3,289 | When are Log scales appropriate? | One other nifty thing about log scales is that they make ratios appear symmetric. For example, like this: | When are Log scales appropriate? | One other nifty thing about log scales is that they make ratios appear symmetric. For example, like this: | When are Log scales appropriate?
One other nifty thing about log scales is that they make ratios appear symmetric. For example, like this: | When are Log scales appropriate?
One other nifty thing about log scales is that they make ratios appear symmetric. For example, like this: |
3,290 | How can I help ensure testing data does not leak into training data? | You are right, this is a significant problem in machine learning/statistical modelling. Essentially the only way to really solve this problem is to retain an independent test set and keep it held out until the study is complete and use it for final validation.
However, inevitably people will look at the results on the... | How can I help ensure testing data does not leak into training data? | You are right, this is a significant problem in machine learning/statistical modelling. Essentially the only way to really solve this problem is to retain an independent test set and keep it held out | How can I help ensure testing data does not leak into training data?
You are right, this is a significant problem in machine learning/statistical modelling. Essentially the only way to really solve this problem is to retain an independent test set and keep it held out until the study is complete and use it for final v... | How can I help ensure testing data does not leak into training data?
You are right, this is a significant problem in machine learning/statistical modelling. Essentially the only way to really solve this problem is to retain an independent test set and keep it held out |
3,291 | How can I help ensure testing data does not leak into training data? | One way to ensure this is to make sure you have coded up all of the things you do to fit the model, even "tinkering". This way, when you run the process repeatedly, say via cross-validation, you are keeping things consistent between runs. This ensures that all of the potential sources of variation are captured by the... | How can I help ensure testing data does not leak into training data? | One way to ensure this is to make sure you have coded up all of the things you do to fit the model, even "tinkering". This way, when you run the process repeatedly, say via cross-validation, you are | How can I help ensure testing data does not leak into training data?
One way to ensure this is to make sure you have coded up all of the things you do to fit the model, even "tinkering". This way, when you run the process repeatedly, say via cross-validation, you are keeping things consistent between runs. This ensur... | How can I help ensure testing data does not leak into training data?
One way to ensure this is to make sure you have coded up all of the things you do to fit the model, even "tinkering". This way, when you run the process repeatedly, say via cross-validation, you are |
3,292 | How can I help ensure testing data does not leak into training data? | I suppose the only way to guarantee this is that someone else has the test data. In a client-consultant relationship this can be managed fairly easily: the client gives the consultant the training set upon which to build the models, and within this training set the consultant can split the data in whatever way necessar... | How can I help ensure testing data does not leak into training data? | I suppose the only way to guarantee this is that someone else has the test data. In a client-consultant relationship this can be managed fairly easily: the client gives the consultant the training set | How can I help ensure testing data does not leak into training data?
I suppose the only way to guarantee this is that someone else has the test data. In a client-consultant relationship this can be managed fairly easily: the client gives the consultant the training set upon which to build the models, and within this tr... | How can I help ensure testing data does not leak into training data?
I suppose the only way to guarantee this is that someone else has the test data. In a client-consultant relationship this can be managed fairly easily: the client gives the consultant the training set |
3,293 | How can I help ensure testing data does not leak into training data? | This is a very good question and a very subtle problem. Of course there are the
bad intentioned mistakes, which derive from someone trying to deceive you. But
there is a deeper question of how to avoid accidental leaking and avoid honest
mistakes.
Let me list some operational good practices. They all stem from honest m... | How can I help ensure testing data does not leak into training data? | This is a very good question and a very subtle problem. Of course there are the
bad intentioned mistakes, which derive from someone trying to deceive you. But
there is a deeper question of how to avoi | How can I help ensure testing data does not leak into training data?
This is a very good question and a very subtle problem. Of course there are the
bad intentioned mistakes, which derive from someone trying to deceive you. But
there is a deeper question of how to avoid accidental leaking and avoid honest
mistakes.
Let... | How can I help ensure testing data does not leak into training data?
This is a very good question and a very subtle problem. Of course there are the
bad intentioned mistakes, which derive from someone trying to deceive you. But
there is a deeper question of how to avoi |
3,294 | How can I help ensure testing data does not leak into training data? | Many important points have been covered in the excellent answers that are already given.
Lately, I've developed this personal check list for statistical independence of test data:
Split data at highest level of data hierarchy (e.g. patient-wise splitting)
Split also independently for known or suspected confounders,... | How can I help ensure testing data does not leak into training data? | Many important points have been covered in the excellent answers that are already given.
Lately, I've developed this personal check list for statistical independence of test data:
Split data at high | How can I help ensure testing data does not leak into training data?
Many important points have been covered in the excellent answers that are already given.
Lately, I've developed this personal check list for statistical independence of test data:
Split data at highest level of data hierarchy (e.g. patient-wise spli... | How can I help ensure testing data does not leak into training data?
Many important points have been covered in the excellent answers that are already given.
Lately, I've developed this personal check list for statistical independence of test data:
Split data at high |
3,295 | How can I help ensure testing data does not leak into training data? | If I remember correctly, some of the forecasting contests (such as Netflix or the ones on Kaggle) use this scheme:
There is a training set, with the "answers".
There is test set #1, for which the researcher provides answers. The researcher finds out their score.
There is test set #2, for which the researcher provides ... | How can I help ensure testing data does not leak into training data? | If I remember correctly, some of the forecasting contests (such as Netflix or the ones on Kaggle) use this scheme:
There is a training set, with the "answers".
There is test set #1, for which the rese | How can I help ensure testing data does not leak into training data?
If I remember correctly, some of the forecasting contests (such as Netflix or the ones on Kaggle) use this scheme:
There is a training set, with the "answers".
There is test set #1, for which the researcher provides answers. The researcher finds out t... | How can I help ensure testing data does not leak into training data?
If I remember correctly, some of the forecasting contests (such as Netflix or the ones on Kaggle) use this scheme:
There is a training set, with the "answers".
There is test set #1, for which the rese |
3,296 | How can I help ensure testing data does not leak into training data? | In some cases, such as Biological sequence-based predictors, it is not enough to ensure that cases do not appear in more than one set. You still need to worry about dependency between the sets.
For example, for sequence-based predictors, one needs to remove redundancy by ensuring that sequences in different sets (incl... | How can I help ensure testing data does not leak into training data? | In some cases, such as Biological sequence-based predictors, it is not enough to ensure that cases do not appear in more than one set. You still need to worry about dependency between the sets.
For e | How can I help ensure testing data does not leak into training data?
In some cases, such as Biological sequence-based predictors, it is not enough to ensure that cases do not appear in more than one set. You still need to worry about dependency between the sets.
For example, for sequence-based predictors, one needs to... | How can I help ensure testing data does not leak into training data?
In some cases, such as Biological sequence-based predictors, it is not enough to ensure that cases do not appear in more than one set. You still need to worry about dependency between the sets.
For e |
3,297 | How can I help ensure testing data does not leak into training data? | I'd say "k-fold cross validation" is the right answer from the theoretical point of view, but your question seems more about organizational and teaching stuff so I'll answer differently.
When people are "still learning" it's often thought as if they're learning how to "quickly and dirtily" apply the algorithms and all... | How can I help ensure testing data does not leak into training data? | I'd say "k-fold cross validation" is the right answer from the theoretical point of view, but your question seems more about organizational and teaching stuff so I'll answer differently.
When people | How can I help ensure testing data does not leak into training data?
I'd say "k-fold cross validation" is the right answer from the theoretical point of view, but your question seems more about organizational and teaching stuff so I'll answer differently.
When people are "still learning" it's often thought as if they'... | How can I help ensure testing data does not leak into training data?
I'd say "k-fold cross validation" is the right answer from the theoretical point of view, but your question seems more about organizational and teaching stuff so I'll answer differently.
When people |
3,298 | How can I help ensure testing data does not leak into training data? | How can I help ensure testing data does not leak into training data?
If you are looking for a practical way to check that the testing data is not the same as the training data I would recommend use of Excel Vlookup or SQL query.
If the dataset is small enough you could use an excel vlookup to check whether the same rec... | How can I help ensure testing data does not leak into training data? | How can I help ensure testing data does not leak into training data?
If you are looking for a practical way to check that the testing data is not the same as the training data I would recommend use of | How can I help ensure testing data does not leak into training data?
How can I help ensure testing data does not leak into training data?
If you are looking for a practical way to check that the testing data is not the same as the training data I would recommend use of Excel Vlookup or SQL query.
If the dataset is smal... | How can I help ensure testing data does not leak into training data?
How can I help ensure testing data does not leak into training data?
If you are looking for a practical way to check that the testing data is not the same as the training data I would recommend use of |
3,299 | Do we need a global test before post hoc tests? | Since multiple comparison tests are often called 'post tests', you'd think they logically follow the one-way ANOVA. In fact, this isn't so.
"An unfortunate common practice is to pursue multiple comparisons only when the hull hypothesis of homogeneity is rejected." (Hsu, page 177)
Will the results of post tests be val... | Do we need a global test before post hoc tests? | Since multiple comparison tests are often called 'post tests', you'd think they logically follow the one-way ANOVA. In fact, this isn't so.
"An unfortunate common practice is to pursue multiple compa | Do we need a global test before post hoc tests?
Since multiple comparison tests are often called 'post tests', you'd think they logically follow the one-way ANOVA. In fact, this isn't so.
"An unfortunate common practice is to pursue multiple comparisons only when the hull hypothesis of homogeneity is rejected." (Hsu, ... | Do we need a global test before post hoc tests?
Since multiple comparison tests are often called 'post tests', you'd think they logically follow the one-way ANOVA. In fact, this isn't so.
"An unfortunate common practice is to pursue multiple compa |
3,300 | Do we need a global test before post hoc tests? | (1) Post hoc tests might or might not achieve the nominal global Type I error rate, depending on (a) whether the analyst is adjusting for the number of tests and (b) to what extent the post-hoc tests are independent of one another. Applying a global test first is pretty solid protection against the risk of (even inadv... | Do we need a global test before post hoc tests? | (1) Post hoc tests might or might not achieve the nominal global Type I error rate, depending on (a) whether the analyst is adjusting for the number of tests and (b) to what extent the post-hoc tests | Do we need a global test before post hoc tests?
(1) Post hoc tests might or might not achieve the nominal global Type I error rate, depending on (a) whether the analyst is adjusting for the number of tests and (b) to what extent the post-hoc tests are independent of one another. Applying a global test first is pretty ... | Do we need a global test before post hoc tests?
(1) Post hoc tests might or might not achieve the nominal global Type I error rate, depending on (a) whether the analyst is adjusting for the number of tests and (b) to what extent the post-hoc tests |
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