Question

What is the difference between a Type I error and a Type II error?

• A. A Type I error is the error of rejecting the null hypothesis when it is true, while a Type II error is the error of failing to reject the null hypothesis when it is false.
• B. A Type I error is the error of accepting the null hypothesis when it is false, while a Type II error is the error of rejecting the null hypothesis when it is true.
• C. A Type I error is the error of overestimating the population mean, while a Type II error is the error of underestimating the population mean.
• D. A Type I error is the error of overestimating the population proportion, while a Type II error is the error of underestimating the population proportion.

Answer 1

The Correct Option is B

The correct option is (B): A Type I error is the error of accepting the null hypothesis when it is false, while a Type II error is the error of rejecting the null hypothesis when it is true.