Q.43
Question
(a) Describe a Type I error and a Type II error in this setting, and explain the consequences of each.
(b) The test has a power of 0.75 to detect that p= 0.45. Explain what this means.
(c) Identify two ways to increase the power in part (b).
Step-by-Step Solution
Verifieda. type I error- null hypothesis rejected even if it's correct and type II error- null hypothesis is not rejected even if it's not correct
b. The true proportion is
c. increase the level of significance and increase the sample size.
The null hypothesis is a run of the mill factual hypothesis which proposes that no factual relationship and importance exists in a bunch of given single noticed variables, between two arrangements of noticed information and estimated peculiarities.
Type I error- null hypothesis rejected even if it's correct
Type II error- null hypothesis is not rejected even if it's not correct
is the probability of rejecting the null hypothesis and the true proportion is .
The two ways to increase the power in part (b) are-
i. increase the level of significance
ii. increase the sample size.