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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We obtain the wrong test statistic
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We reject the null hypothesis when it is actually true
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We fail to reject the null hypothesis when it’s actually false
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We reject the alternate hypothesis when it’s actually true
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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: -A type I error occurs when in research when we reject the null hypothesis and erroneously state that the study found significant differences when there indeed was no difference. In other words, it is equivalent to saying that the groups or variables differ when, in fact, they do not or having false positives.
Detailed explanation-3: -Type I error is the probability of rejecting the null when it is true is TRUE. A type I error is also known as the error of false rejection. That is, when a type I error occurs, the statistician incorrectly rejects the null hypothesis even though it is true.