What does the 'p' - value in hypothesis testing represent?

The Correct answer is The probability of rejecting the null hypothesis when it is true.

Key Points

• In statistical hypothesis testing, the P-value, or probability value, measures the likelihood that a test statistic is as extreme or more extreme than the value obtained, assuming the null hypothesis is true.
• It indicates how probable it is that the observed results occurred by chance.
• A smaller P-value suggests stronger evidence to reject the null hypothesis.
• In hypothesis testing, the P-value is compared to a predefined alpha level (significance level) to determine whether to reject the null hypothesis.
• The P-value approach allows researchers to assess statistical significance and decide if the observed difference is meaningful based on the calculated probability.
• P-values are expressed as decimals and can be converted into percentages.
• For instance, a P-value of 0.0237 represents a 2.37% chance that the results are due to random variation.
• Generally, a P-value less than 0.05 is considered statistically significant, indicating that the null hypothesis may be rejected.