Practice P-Value in Statistics

Use these practice problems to test your method after reviewing the concept explanation and worked examples.

Quick Recap

The p-value is the probability of observing results at least as extreme as the actual data, calculated under the assumption that the null hypothesis is true. A small p-value (typically below 0.05) suggests the observed data is unlikely under the null, providing evidence against it.

P-value answers: 'If nothing special is really happening, how surprising is my data?' A tiny p-value (like 0.01) means your results would be very rare if the null were true - so maybe the null is wrong. A large p-value means your results aren't surprising under the null.

Showing a random 20 of 76 problems.

Example 1

hard
A two-tailed z-test gives z=2.65z = -2.65. The p-value is approximately 0.008. If α=0.05\alpha = 0.05, should we reject H0H_0?

Example 2

medium
Statistical significance and practical significance can differ; a very small effect can still produce a small p-value with a ____ sample.

Example 3

hard
A study tests 4040 outcomes at α=0.05\alpha = 0.05 but all H0H_0 are true. Expected number of 'significant' results is what?

Example 4

hard
Five tests at family-wise α=0.05\alpha = 0.05 via Bonferroni: each test uses α=\alpha = what?

Example 5

medium
Why does running many tests and reporting only the smallest p-value distort its meaning?

Example 6

challenge
A meta-analysis combines kk independent p-values via Fisher's method using 2ln(pi)-2 \sum \ln(p_i). Under H0H_0, this statistic follows what distribution?

Example 7

medium
A one-sided test has z=1.0z=1.0, with upper-tail area about 0.16. Is this evidence against H0H_0 at α=0.05\alpha=0.05?

Example 8

easy
At α=0.05\alpha = 0.05, a p-value of 0.200.20 leads to what decision?

Example 9

easy
True or false: smaller p-values mean larger effects.

Example 10

challenge
An exact one-sided permutation p-value uses the proportion of permutations with statistic tobs\ge t_\text{obs}. If 2020 of 10001000 permutations meet this, the p-value is ____.

Example 11

easy
At α=0.05\alpha = 0.05, a p-value of 0.020.02 leads to what decision?

Example 12

easy
What threshold is most commonly used to call a p-value 'small'?

Example 13

medium
Why do statisticians prefer to report the exact p-value (e.g., 0.012) instead of just 'p < 0.05'?

Example 14

easy
Fill in: the p-value measures how ____ the data are, assuming the null is true.

Example 15

medium
A study has p=0.001p=0.001 for a tiny effect (Δ=0.1\Delta = 0.1 on a 100-point scale) with n=10000n=10000. Is the effect important?

Example 16

medium
Two studies report p =0.049=0.049 and p =0.051=0.051 at α=0.05\alpha=0.05. How different is the actual evidence?

Example 17

medium
A one-sided test of Ha:μ>0H_a:\mu>0 gives z=2.33z=2.33, with upper-tail area about 0.01. At α=0.05\alpha=0.05, decide.

Example 18

hard
Two independent studies report p=0.04p=0.04 for the same hypothesis. Should we combine them by multiplying p-values?

Example 19

challenge
Experiment A: p =0.04=0.04, n=2,000,000n=2{,}000{,}000. Experiment B: p =0.04=0.04, n=20n=20. Why might A's significant result be less impressive than B's?

Example 20

medium
True or false: a p-value above α\alpha means H0H_0 is true.