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Debunking wrong CLT statement

normal-distribution convergence intuition central-limit-theorem communication asked Jun 22, 2020 at 16:14

stats.stackexchange.com

27 votes

Proper scoring rule when there is a decision to make (e.g. spam vs ham email)

machine-learning classification model-evaluation accuracy scoring-rules asked May 5, 2020 at 13:30

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24 votes

Area under the ROC curve when there is imbalance: is there a problem, and if not, why does this rumor exist?

machine-learning classification unbalanced-classes roc auc asked Aug 31 at 16:37

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22 votes

(Why) Is absolute loss not a proper scoring rule?

machine-learning classification loss-functions supervised-learning scoring-rules asked Jun 23, 2020 at 22:42

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20 votes

Why does regularization wreck orthogonality of predictions and residuals in linear regression?

machine-learning least-squares residuals regularization supervised-learning asked Oct 29, 2020 at 17:26

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15 votes

If we shouldn't do post hoc power calculations, are post hoc effect size calculations also invalid?

hypothesis-testing statistical-power effect-size post-hoc equivalence asked Apr 26, 2021 at 16:48

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14 votes

Fourier transform is an isomorphism...but we don’t get when each frequency appears?

fourier-transform asked Dec 11, 2019 at 11:12

dsp.stackexchange.com

13 votes

Allocating credit card points

optimization integer-programming finance knapsack asked Sep 19, 2019 at 1:43

or.stackexchange.com

13 votes

Power paradox: overestimated effect size in low-powered study, but the estimator is unbiased

hypothesis-testing statistical-power bias effect-size paradox asked Nov 8, 2022 at 14:23

stats.stackexchange.com

12 votes

What is the algebra showing the logistic and log loss to be equivalent?

regression machine-learning probability classification loss-functions asked Mar 16 at 18:06

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Top Answers

Why do we worry about overfitting even if "all models are wrong"?

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Why don't linear regression assumptions matter in machine learning?

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Is it a scam if someone asks for my full name, email, and bank name?

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Is there a 1 in 20 or 1 in 400 chance of guessing the outcome of a d20 roll before it happens?

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Why are the numbers on a ball in a lotto draw categorical nominal instead of categorical ordinal?

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How to explain 1.5 children?

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What if a non-random sample is identical to a random sample?

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Overfitting, but why is the training deviance dropping?

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What are the myths associated with linear regression, data transformations?

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Is "not independent" the same as "dependent" in English?

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Proof that variance is always greater than or equal to zero

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Do we actually take random line in first step of linear regression?

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Is the CDF of the Mean always 0.5 for all kind of distributions?

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How would I bias my binary classifier to prefer false positive errors over false negatives?

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How to test whether a correlation is equal to 1?

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When we calculate mean and variance, do we assume data are normally distributed?

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If a data set appears to be normal after some transformation is applied, is it really normal?

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A smaller dataset is better: Is this statement false in statistics? How to refute it properly?

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Why don’t we calculate the average of an entire given population instead of computing confidence interval to estimate the population mean?

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Probability of a coin being two-headed given it lands on heads

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Why are standard frequentist hypotheses so uninteresting?

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Meaning of "Overdispersion" in Statistics

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Is Logistic Regression a classification or prediction model?

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Can predictive models make predictions for individuals or only for groups?

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Is probability equal about the mean?

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What are the disadvantages of accuracy?

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An example of a SYMMETRIC distribution with finite mean but infinite/undefined variance?

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How would you write mathematically that a random variable follows some unknown distribution?

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How does PCA behave when there is no correlation in the dataset?

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What are the worst (commonly adopted) ideas/principles in statistics?

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