COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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The null is true, but we mistakenly reject it.
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The null is false and we reject it.
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The null is false, but we fail to reject it.
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The null is true but we fail to reject it.
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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: -Answer and Explanation: The statement (a.) Type I error is the probability of rejecting the null when it is true is TRUE.
Detailed explanation-4: -A type I error is a false positive leading to an incorrect rejection of the null hypothesis.
Detailed explanation-5: -Type I Error. Rejecting the null hypothesis when it is in fact true is called a Type I error. Many people decide, before doing a hypothesis test, on a maximum p-value for which they will reject the null hypothesis.