Question

A Type II error, or a false negative, refers to a situation when:

a) The null hypothesis is rejected when it is true
b) The null hypothesis is accepted when it is false
c) The alternative hypothesis is rejected when it is true
d) Both hypotheses are accepted

Answer 1

A Type II error occurs when a false null hypothesis is not rejected, denoted by beta (β) in statistics.

Step-by-step explanation:

A Type II error, or a false negative, refers to a situation when the decision is not to reject the null hypothesis when, in fact, the null hypothesis is false. In statistical hypothesis testing, this can be a crucial error as it leads to the incorrect conclusion that there is no effect or difference when one actually exists. The probability of making a Type II error is denoted by the Greek letter beta (β), and efforts are often made in statistical testing to minimize this probability along with the probability of making a Type I error, which happens when the null hypothesis is incorrectly rejected.