If the p-value is greater than the alpha level, the conclusion is to:

If the p-value is greater than the alpha level, the conclusion is to:

• A. Reject the null hypothesis
• B. Fail to reject the null hypothesis
• C. Accept the alternative
• D. Conclude the effect is large

Answer: (B)

When deciding about a hypothesis test, the p-value measures how compatible the observed data are with the null hypothesis. If this probability is greater than the preselected significance level, the data aren’t unusual enough to rule out the null at that level, so you fail to reject the null hypothesis. It’s important to recognize that this does not prove there is no effect or that the null is true; it simply means there isn’t enough evidence to declare a statistically significant effect given the data and the chosen alpha. The p-value doesn’t tell you about the size of any effect—that would require looking at the effect estimate and its confidence interval.

When deciding about a hypothesis test, the p-value measures how compatible the observed data are with the null hypothesis. If this probability is greater than the preselected significance level, the data aren’t unusual enough to rule out the null at that level, so you fail to reject the null hypothesis. It’s important to recognize that this does not prove there is no effect or that the null is true; it simply means there isn’t enough evidence to declare a statistically significant effect given the data and the chosen alpha. The p-value doesn’t tell you about the size of any effect—that would require looking at the effect estimate and its confidence interval.