Does a p-value of 0.1 mean that 1% of the time, the amount of deviation seen between observed and expected values could occur due to chance alone?

Clarification of P-Value Concept

1. Understanding the P-Value: A p-value is a statistical measure that helps scientists determine the significance of their research results. It indicates the probability of obtaining results at least as extreme as the observed results, assuming that the null hypothesis is true.

2. Interpretation of a P-Value of 0.1: A p-value of 0.1 means there is a 10% chance of observing the results, or something more extreme, due to random variation alone if the null hypothesis is true. This does not imply that 1% of the time the deviation occurs due to chance; rather, it indicates that 10% is the probability of observing such a deviation purely due to chance.

3. Common Misconceptions: It is crucial to avoid misconceptions regarding the p-value. A p-value does not measure the probability that the null hypothesis is true or the probability of making a mistake if we reject the null hypothesis. It purely reflects the probability of observing the data, or something more extreme, under the assumption of no true effect (i.e., the null hypothesis).

Summary

In summary, a p-value of 0.1 indicates a 10% probability that the observed results could occur due to chance if the null hypothesis is true, not 1%. Understanding the correct interpretation of p-values is critical in statistical analysis and hypothesis testing.