METHODS OF DATA ANALYSIS
DECISION MAKING WITH HYPOTHESIS TESTING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Failing to reject a null hypothesis that is false can be characterized as
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a Type I error
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a Type II error
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both a Type I and Type II error
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no error
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Explanation:
Detailed explanation-1: -A type I error (false-positive) occurs if an investigator rejects a null hypothesis that is actually true in the population; a type II error (false-negative) occurs if the investigator fails to reject a null hypothesis that is actually false in the population.
Detailed explanation-2: -When doing hypothesis testing, two types of mistakes may be made and we call them Type I error and Type II error. If we reject the null hypothesis when it is true, then we made a type I error. If the null hypothesis is false and we failed to reject it, we made another error called a Type II error.
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