In hypothesis testing, what is the alpha value used for?

• A. Set the threshold for statistical significance
• B. Determine the sample size
• C. Calculate the p-value
• D. Describe the data distribution

Answer: (A)

Alpha is the threshold researchers set before collecting data to decide when a result is considered statistically significant. It represents the maximum acceptable chance of a false positive—rejecting the null hypothesis when it is actually true. When you conduct a test, you compare the p-value to this preselected threshold. If the p-value is at or below the threshold, you declare the result significant and reject the null hypothesis; if it’s above, you do not reject it. Common choices are 0.05 or 0.01, but the exact value reflects how willing you are to risk a false positive. This value does not determine sample size, it is not the p-value itself, and it does not describe the data distribution.