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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the probability of committing a Type II error
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the probability of committing a Type I error
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the probability of either a Type I or Type II, depending on the hypothesis to be tested
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None of the above
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Detailed explanation-1: -The probability of making a type II error (failing to reject the null hypothesis when it is actually false) is called (beta). The quantity (1-) is called power, the probability of observing an effect in the sample (if one), of a specified effect size or greater exists in the population.
Detailed explanation-2: -Yes, a change in the alpha level will affect a type II error in the opposite direction. The alpha level (level of significance) is equal to the type I error, which is defined as the probability of rejecting the true null hypothesis. A Type II error is the probability of not rejecting the false null hypothesis.
Detailed explanation-3: -Simply put, power is the probability of not making a Type II error, according to Neil Weiss in Introductory Statistics. Mathematically, power is 1 – beta. The power of a hypothesis test is between 0 and 1; if the power is close to 1, the hypothesis test is very good at detecting a false null hypothesis.
Detailed explanation-4: -The probability of the type I error (a true null hypothesis is rejected) is commonly called the significance level of the hypothesis test and is denoted by . The probability of a type II error (a false null hypothesis is not rejected) is denoted by .