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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beta error
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alpha error
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critical value error
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None of the above
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Detailed explanation-1: -The probability of committing a type I error (rejecting the null hypothesis when it is actually true) is called (alpha) the other name for this is the level of statistical significance.
Detailed explanation-2: -A Type I error is often represented by the Greek letter alpha () and a Type II error by the Greek letter beta ( ). In choosing a level of probability for a test, you are actually deciding how much you want to risk committing a Type I error-rejecting the null hypothesis when it is, in fact, true.
Detailed explanation-3: -Alpha risk is the risk that in a statistical test a null hypothesis will be rejected when it is actually true. This is also known as a type I error, or a false positive. The term “risk” refers to the chance or likelihood of making an incorrect decision.
Detailed explanation-4: -Review: Error probabilities and So using lower values of can increase the probability of a Type II error. A Type II error is when we fail to reject a false null hypothesis. Higher values of make it easier to reject the null hypothesis, so choosing higher values for can reduce the probability of a Type II error.