A researcher looks at the mean salaries of male and female electricians and decides based on the evidence that there is no difference between the two groups. Given that there was a failure to reject the null hypothesis, it is possible that a type II error was made. Given the type of error made in this situation, what could researchers do to reduce the risk of this error?

Explanation:

Type 2 error occurs when a null hypothesis is accepted even when it is not true.

To avoid type 2 error the sample size can be increase. Iarge sample size help capture enough variation that may occur among the variables to be used reduced the amount of error in the experiment.

The significant level for prediction of accuracy should be increased for sciences it is often recommended that p<_ 0.05 to 0.01 to reduce to risk associated with error.

Good experimental layout can also help reduce the risk of type 2 error, the method of collecting data and data to be collected, field layout should be well structured to avoid bias.

well, i can't read it so i'll ask you questions about it : )

if you were a reader and you read the introduction, would you want to read more?

does it start with a question? if so, is it something you would want to read about?

and ask any friends or family for their opinion : )