Practice question · Select all that apply
Select every statement that is TRUE about hypothesis testing.
Hints
- Two options are false - one misdefines a p-value, one treats 0.05 as a cliff.
- The p-value is not the probability H0 is true, and 0.049 vs 0.051 barely differ.
Show the answer
- B. A Type II error is failing to detect a real effect.
- C. The alpha level directly sets the Type I error rate.
- E. Statistical power typically rises with larger sample sizes.
Why
Alpha setting the Type I rate, Type II as a miss, and power rising with sample size are all true. A p-value is not the probability the null is true, and results just either side of 0.05 are nearly identical - the two false options are classic misreadings.
Practise Statistical Significance
The app has 6 more questions on this lesson, and keeps your place in the course. Psychology I is free to start.
More questions on Statistical Significance
- Sort each statement about p-values as a correct interpretation or a misinterpretation.
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- A result with p = 0.049 and a result with p = 0.051 tell you almost the same thing about the world, even…