Question

TRUE/FALSE. Explain.

1.) Power + B (beta) = 1

2.) You can increase power and decrease (Alpha) at the same time by increasing sample size.

3.) alpha= 1- beta

4.) alpha is the significance level and the probability of type II error

5.)Type II error is rejection the null when the null is true.

6.)There is more than one way to increase power.

7.)Statistical significance implies practical significance.

Answer 1

(1) TRUE because power = 1- beta or power + beta= 1

(2) FALSE, because power and alpha are directly proportional to sample size, i.e. when sample size increases, both power and alpha increases and vice versa

(3) FALSE, because alpha is not equal to 1 -beta, but power = 1-beta

(4) False, because alpha is the probability of type I error

(5) False, rejecting the null hypothesis when it is true is type 1 error

(6) TRUE, we can increase power by sample size, significance level, etc.

(7) False, statistical significance never implies pratical significance