An experiment resulted in a p-value of 0.5. Which statement is true?

An experiment resulted in a p-value of 0.5. Which statement is true?

• A. The test results were statistically significant at a 5% level.
• B. 50% of the test subjects experienced dizziness after the test.
• C. Patients experienced 50% less dizziness as a result of the treatment.
• D. The probability that such a test statistic value occurs by chance alone is 50%.

Answer: (D)

The p-value represents the probability of obtaining results at least as extreme as those observed in the study, assuming that the null hypothesis is true. A p-value of 0.5 indicates that there is a 50% chance of observing the data (or something more extreme) due to random variation alone, under the null hypothesis. This means that the evidence against the null hypothesis is weak, and researchers would typically fail to reject the null hypothesis at conventional levels of significance (such as 0.05). Hence, stating that the probability that such a test statistic value occurs by chance alone is 50% accurately reflects the meaning of the p-value in this context. This shows a lack of statistical significance, suggesting that the treatment or effect being tested does not have strong evidence to support its effectiveness in the population being studied.

The p-value represents the probability of obtaining results at least as extreme as those observed in the study, assuming that the null hypothesis is true. A p-value of 0.5 indicates that there is a 50% chance of observing the data (or something more extreme) due to random variation alone, under the null hypothesis. This means that the evidence against the null hypothesis is weak, and researchers would typically fail to reject the null hypothesis at conventional levels of significance (such as 0.05).

Hence, stating that the probability that such a test statistic value occurs by chance alone is 50% accurately reflects the meaning of the p-value in this context. This shows a lack of statistical significance, suggesting that the treatment or effect being tested does not have strong evidence to support its effectiveness in the population being studied.