EDUCATION UGC NET
RESEARCH METHODOLOGY
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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the null hypothesis is rejected even though it is true
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the null hypothesis is accepted even though it is false
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both the null hypothesis as well as alternative hypothesis are rejected
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None of the above
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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 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-3: -If we reject the null hypothesis, we are stating that our data are so unexpected that they are inconsistent with the null hypothesis. Our decision will change our behavior. If we reject the null hypothesis, we will act as if the null hypothesis is false, even though we do not know if that is in fact false.
Detailed explanation-4: -A type I error occurs when the null hypothesis, which is the belief that there is no statistical significance or effect between the data sets considered in the hypothesis, is mistakenly rejected. The type I error should never be rejected even though it’s accurate. It is also known as a false positive result.
Detailed explanation-5: -What causes type 1 errors? Type 1 errors can result from two sources: random chance and improper research techniques. Random chance: no random sample, whether it’s a pre-election poll or an A/B test, can ever perfectly represent the population it intends to describe.