Question

Question 1 (1 point)

True or False:

The power of a test is the probability of rejecting the null hypothesis when the null is false.

Question 1 options:

	True
	False

Question 2 (1 point)

What type of error occurs when a false null hypothesis is not rejected?

Question 2 options:

	Type I
	Type II
	Type III
	Rejection Error

Question 3 (1 point)

Which type of error results in a "false alarm?"

Question 3 options:

	Type I
	Type II
	Type III
	Rejection Error

Question 4 (1 point)

Saved

What is the notation for "significance level?"

Question 4 options:

	α{"version":"1.1","math":"\alpha"}
	ν{"version":"1.1","math":"\nu"}
	σ{"version":"1.1","math":"\sigma"}
	ρ{"version":"1.1","math":"\rho"}

Question 5 (1 point)

True or False:

Sampling variability refers to the amount that a statistic changes over multiple instances/samples.

Question 5 options:

	True
	False

Answer 1

(1) it is true because the power of a test is opposite of type II error. Type II error is the probability of not rejecting the false null hypothesis, so power is the probability of rejecting the null hypothesis, when it is false

(2) Type II error is the probability of not rejecting the false null hypothesis, so the correct answer is TYPE II

(3) correct answer is type I error because type I error results in rejection of a true null hypothesis, i.e. alarming at the wrong time when it is not required.

(4) notation for significance level is alpha, so option A is correct. Sigma, nu and rho represent standard deviation and correlation etc.

(5) yes, it is true because the sampling variability is the change in the sample statistic based on different samples taken for the calculation.