Question

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

a. 0.1
b. 0.01
c. 0.5
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 (or 5%) is a very common threshold. It strikes a balance between being too lenient (which would lead to more Type - I errors if $\alpha$ is large, like 0.1 or 0.5) and too strict (if $\alpha$ is very small like 0.01). With $\alpha = 0.05$, we are willing to accept a 5% chance of making a Type - I error.

Answer:

d. 0.05