Stats Hypothesis testing

Question 1

Type 1 error

Answer 1

Type I: the null hypothesis is rejected when it is true (finding a difference that didn’t exist), this is also called a false positive. This is determined against a preset significance level (termed alpha). As the significance level is determined in advance the chance of making a type I error is not affected by sample size.

Question 2

Type 2 error

Answer 2

Type II: the null hypothesis is accepted when it is false (failing to find a difference that really existed), this is also called a false negative. The probability of making a type II error is termed beta. It is determined by both sample size and alpha.

Question 3

Power

Answer 3

The power of a study is the probability of (correctly) rejecting the null hypothesis when it is false

Power = 1 - the probability of a type II error
Power can be increased by increasing the sample size