Question

1. what is the primary reason for setting a significance level before conducting a hypothesis test?

a. to decide the threshold for rejecting the null hypothesis.
b. to calculate the mean of the sample data.
c. to determine the sample size needed for the study.
d. to choose the appropriate statistical test.

Explanation:

The significance level ($\alpha$) in a hypothesis test is the probability of rejecting the null hypothesis when it is actually true (Type - I error). It acts as a threshold. If the p - value (probability of obtaining the test statistic or more extreme results assuming the null hypothesis is true) is less than the significance level, we reject the null hypothesis.

• Option b: Calculating the sample mean is not related to the significance level. The sample mean is part of the data - summary for the sample.
• Option c: Sample size determination is a separate concept, often based on factors like power of the test, expected effect size, etc., not directly on the significance level.
• Option d: The choice of statistical test depends on the type of data (categorical or numerical), study design (paired or independent samples etc.), not on the significance level.

Answer:

A. To decide the threshold for rejecting the null hypothesis.