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confidence intervals
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Why can a CI for Cohen's d include zero when the t test is significant?
Why an effect size interval for Cohen's d can cross zero while the mean difference interval does not, and which d and interval agree with the test.
Read the answer →Confidence interval for eta squared: does the Fisher z shortcut work?
Why the Fisher z shortcut gives unreliable intervals for eta squared, and how to get an exact one from F and its degrees of freedom.
Read the answer →Mann-Whitney effect size: is z/√N right, and which CI should you report?
Why z/√N is a shaky effect size for Mann-Whitney, why Fisher's z interval does not suit it, and which effect sizes and intervals to report instead.
Read the answer →What should you do after rejecting the null hypothesis?
A significant result is a starting point, not a conclusion. Estimate the effect, check that it is robust, and replicate before you treat it as established.
Read the answer →Standard error vs standard deviation: what is the difference?
The SD describes how individual values vary; the standard error describes how a sample mean varies. How to tell which one you need, totals included.
Read the answer →Is a non-significant result from a large study evidence for the null?
When failing to reject the null hypothesis tells you something, why the p value alone cannot show it, and how equivalence tests make the case.
Read the answer →Why does bootstrapping work? A plain-language explanation
Resampling your own data sounds like cheating, yet the bootstrap gives honest standard errors. Here is the idea in everyday terms.
Read the answer →Is there a 95% probability that your confidence interval covers the true mean?
The 95% describes the method that builds the interval, not the one interval you computed. Here is why that distinction matters, and when it does not.
Read the answer →Where does the 1/sqrt(n) margin of error come from?
The rule that a poll has a margin of error of about 1/sqrt(n) is a short derivation, not a guess. Here it is step by step.
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