Practice question · Multiple choice
A study reports p = 0.03. Why is it wrong to conclude there is a 3% chance the null hypothesis is true, and what does the 3% actually refer to?
Hints
- Ask what has to be assumed before a p-value can be calculated at all.
- P(data | null) and P(null | data) are different quantities. Which one did the test compute?
Show the answer
B. Because the p-value is computed by assuming the null is true.
Why
The calculation begins by assuming the null is true, so it cannot deliver a probability that it is false, the output would contradict its own input. And the two quantities can differ wildly depending on prior plausibility: a low p-value on a wild claim is far likelier to be one of the 3% than a discovery.
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.
- A researcher analysing one dataset can choose which outliers to drop, which covariates to include and when to…
- Select every statement that is TRUE about hypothesis testing.
- A result with p = 0.049 and a result with p = 0.051 tell you almost the same thing about the world, even…