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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level of significance
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Type II error
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critical value
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Type I error
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Detailed explanation-1: -when we reject true null hypothesis, this will be a TYPE I error . When the null hypothesis has been true, but the sample information has resulted in the rejection of the null, a TYPE I ERROR has been made.
Detailed explanation-2: -In hypothesis testing, two types of wrong decisions can occur. If the null hypothesis is true, but we reject it, the error is a type I error. If the null hypothesis is false, but we fail to reject it, the error is a type II error.
Detailed explanation-3: -A Type I error means rejecting the null hypothesis when it’s actually true. It means concluding that results are statistically significant when, in reality, they came about purely by chance or because of unrelated factors. The risk of committing this error is the significance level (alpha or ) you choose.
Detailed explanation-4: -When a null hypothesis is not rejected, it is correct to say that there is no possibility of making a Type I error. A Type I error can only occur when a researcher chooses to reject the null hypothesis. The type of error which can occur when a null hypothesis is not rejected, is called the Type II error.