Question

1. what is the commonly used significance level (a) threshold in hypothesis testing?

a. 0.5
b. 0.1
c. 0.01
d. 0.05

Explanation:

In hypothesis testing, the significance level ($\alpha$) represents the probability of rejecting the null hypothesis when it is actually true (Type - I error). A significance level of 0.05 is widely used in many fields. It strikes a balance between being too lenient (a higher $\alpha$ like 0.1 or 0.5 would increase the Type - I error rate) and too strict (a very low $\alpha$ like 0.01 would make it harder to detect real effects).

Answer:

d. 0.05