Question:

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

Updated On: Aug 5, 2024
  • 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.
  • 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.
  • 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.
  • 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.
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The Correct Option is A

Solution and Explanation

The correct option is (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.
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