If p = 0.18, which interpretation is correct?

If p = 0.18, which interpretation is correct?

• A. There is an 18% probability that differences are due to chance
• B. The results are statistically significant
• C. The null hypothesis is false with 18% certainty
• D. The study has 18% power

Answer: (A)

The main idea here is how to interpret a p-value. A p-value of 0.18 means that, if there were really no difference (the null hypothesis is true), there is about an 18% chance of obtaining results as extreme as the ones observed. In other words, the data are not highly incompatible with the null, so the observed differences could arise by random sampling alone, about 18% of the time. This interpretation focuses on what the p-value says about the data under the null, not on the probability that the null is true or false in the population, nor on the study’s power. That’s why the statement about an 18% probability that the differences are due to chance is the best fit. It’s also why the other options aren’t correct: a p-value of 0.18 does not by itself declare significance, it does not give the probability that the null is false, and it does not reflect the study’s power.

The main idea here is how to interpret a p-value. A p-value of 0.18 means that, if there were really no difference (the null hypothesis is true), there is about an 18% chance of obtaining results as extreme as the ones observed. In other words, the data are not highly incompatible with the null, so the observed differences could arise by random sampling alone, about 18% of the time.

This interpretation focuses on what the p-value says about the data under the null, not on the probability that the null is true or false in the population, nor on the study’s power. That’s why the statement about an 18% probability that the differences are due to chance is the best fit. It’s also why the other options aren’t correct: a p-value of 0.18 does not by itself declare significance, it does not give the probability that the null is false, and it does not reflect the study’s power.