Which of following is true about Type I error? O The alpha (x) level False negative Rejecting the null hypothesis when in reality it is false. Accepting (not rejecting) the null hypothesis when in reality it is false.
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- Type-II error is? A. Rejecting the null hypothesis when it is actually true B. Not rejecting the null hypothesis when its actually false C. Accepting the null hypothesis when its actually false D. Rejecting the alternative hypothesis it is actually falseWhat type of error(s) occur(s) when we reject the null hypothesis when the null hypothesis is true? OA. Type 1 Error OB. Type II Error OC. Both Type I and Type II Errors OD. Neither Type I nor Type II ErrorType I error is when you end up rejecting the null hypothesis as a result of the statistical testing, when in fact the null hypothesis is actually ____."
- If we fail to reject the null hypothesis when the alternative hypothesis is true, we have made a O type a error. O type B error. O type I error. O type II error. O correct decision.True or False: A Type I Error is made by failing to reject the null hypothesis when the null hypothesis is actually incorrect.Which of following is not true about Type I error? The alpha (x) level False positive Rejecting the null hypothesis when in reality it is true. Accepting (not rejecting) the null hypothesis when in reality it is false.
- Which of the following relates to the rejection of the null hypothesis when it is actually true? 1. Type I error2. Type II error 3. Power 4. Statistical significanceWhich of the following is an accurate definition of a type 2 error? rejecting a false null hypothesis rejecting a true null hypothesis failing to reject a false null hypothesis failing to reject a true null hypothesisSuppose the null hypothesis, H0, is: a patient is not sick. State the Null and Alternative Hypothesis. Which type of error has the greater consequence, Type I or Type II?
- Which of the following relates to the rejection of the null hypothesis when it is actually false? 1. Type I error 2. Type II error 3. Power 4. Statistical significanceWhich of the following is an example of a Type 2 error? Rejecting a false null hypothesis. Rejecting a true null hypothesis. Failing to reject a false null hypothesis. Failing to reject a true null hypothesis.A company that develops artificial intelligence designed to detect false statements has developed a program that police officers can use to determine whether a criminal suspect is lying or not. According to the company, the AI can detect false statements correctly 75% of the time. What are the null and alternative hypothesis for testing the claim that the AI detects false statements as claimed by the company? H0 : p = .01, Hα : p ≠ .01 H0 : p = .99, Hα : p ≠ .99 H0 : p = .25, Hα : p ≠ .25 H0 : p = .75, Hα : p ≠ .75