When a retail team introduces a new marketing approach to boost sales and sales do improve, but the statistical outcome suggests there is no meaningful change, what is this phenomenon called?
Assuming a small sample invalidates the findings
Type I error
Mistaking a correlation test for a significance procedure
A type II error occurs when an actual effect goes undetected and the null hypothesis is not rejected despite a real difference. Conversely, a type I error happens when the null hypothesis is incorrectly rejected, detecting a difference that is not present.
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What is the difference between Type I and Type II errors?
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What is a null hypothesis in the context of errors in hypothesis testing?