In response to a reported outbreak with a p-value of 0.01, what decision should be made at alpha = 0.05?

In response to a reported outbreak with a p-value of 0.01, what decision should be made at alpha = 0.05?

• A. Do not reject the null hypothesis
• B. Reject the null hypothesis
• C. Accept the alternative hypothesis
• D. Data are insufficient to decide

Answer: (B)

In hypothesis testing, you compare the p-value to your chosen significance level to decide whether to reject the null. A p-value of 0.01 means that if there were no real outbreak effect, you'd expect to see results as extreme as observed only about 1% of the time. With a significance level of 0.05, any p-value smaller than 0.05 is considered statistically significant. Since 0.01 is less than 0.05, you reject the null hypothesis. This indicates evidence against no outbreak effect at the 5% level. It’s not about proving the alternative; it’s about concluding that the observed result is unlikely under the null. Here, the data are sufficient to decide at this significance level, leading to rejecting the null.

In hypothesis testing, you compare the p-value to your chosen significance level to decide whether to reject the null. A p-value of 0.01 means that if there were no real outbreak effect, you'd expect to see results as extreme as observed only about 1% of the time. With a significance level of 0.05, any p-value smaller than 0.05 is considered statistically significant. Since 0.01 is less than 0.05, you reject the null hypothesis. This indicates evidence against no outbreak effect at the 5% level. It’s not about proving the alternative; it’s about concluding that the observed result is unlikely under the null. Here, the data are sufficient to decide at this significance level, leading to rejecting the null.