When a hypothesis test is being carried out, there are four different situations thatcan occur depending on the truthfulness of the null hypothesis. Type I error occurswhen the following situation happenThe null hypothesis is false, but we mistakenly fail to reject it.The null hypothesis is true, but we mistakenly reject it.The null hypothesis is false, and we reject it.The null hypothesis is true, and we fail to reject it.

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Answered: When a hypothesis test is being carried…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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How do you know when to reject the hypothesis and when to fail to reject it, and whether there is -or is not -sufficient evidence to support a claim?
A type I error A. arises when the false null hypothesis is not rejected. OB. is the rejection of a true null hypothesis. C. arises when the true null hypothesis is not rejected. O D. is the rejection of a false null hypothesis.
Which of the following is not one of the four steps of the hypothesis test? A. State the level of significance, choose a test, and check the conditions for the test B. Make a decision to reject or not reject the null hypothesis C. State the null and alternative hypothesis about the population parameter D. All of the these are steps of the hypothesis test
Food inspectors inspect samples of food products to see if they are safe. This can be thought of as a hypothesis test with the following hypotheses. Họ: the food is safe H3: the food is not safe The following is an example of what type of error? The sample suggests that the food is safe, but it actually is not safe. type I O type II O not an error
Which of the below-mentioned hypotheses is assumed to be true while we perform a hypothesis test?
What is a type I and a type II error? Select one: A. A type I error is the mistake of rejecting the null hypothesis when the null hypothesis is actually true. A type II error is the mistake of failing to reject the null hypothesis when the null hypothesis is actually false. B. A type I error is the mistake of failing to reject the null hypothesis when the null hypothesis is actually false. A type II error is the mistake of rejecting the null hypothesis when the null hypothesis is actually true. C. A type I error is the mistake of rejecting the null hypothesis when the null hypothesis is actually false. A type II error is the mistake of failing to reject the null hypothesis when the null hypothesis is actually true. D. A type I error is the mistake of failing to reject the null hypothesis when the null hypothesis is actually true. A type II error is the mistake of rejecting the null hypothesis when the null hypothesis is actually false
A Type I error is defined as a. rejecting a null hypothesis when it is in fact true b. rejecting a false null hypothesis c. failing to reject a true null hypothesis d. failing to reject a false null hypothesis
Develop the analysis of variance computations for the following completely randomized design. At a = 0.05, is there a significant difference between the treatment means? 2 A 135 119 114 106 132 115 129 94 118 Treatment B 107 114 124 104 108 110 96 113 103 81 106 с 91 83 86 101 89 116 109 119 98 98 99 193.14 132.89 153.78
2. Can hypothesis testing ever prove a hypothesis true? How should we interpret an experiment where we fail to reject the null hypothesis?
(d) Decide whether to reject or fail to reject the null hypothesis. O A. Fail to reject H, because the test statistic is in the rejection region(s). O B. Reject H, because the test statistic is not in the rejection region(s). O C. Fail to reject Ho because the test statistic is not in the rejection region(s). D. Reject Ho because the test statistic is in the rejection region(s). (e) Interpret the decision in the context of the original claim. A. At the 5% level of significance, there is sufficient evidence to reject the claim that the mean price is $24,000. B. At the 5% level of significance, there is not sufficient evidence to reject the claim that the mean price is $24,000. C. At the 5% level of significance, there is sufficient evidence to reject the claim that the mean price is not $24,000. O D. At the 5% level of significance, there is not sufficient evidence to reject the claim that the mean price is not $24,000.
Which of the following below could be the null hypothesis ? ( look at the image )
What is a type I error? What is a type II error? Choose the correct answer below. C.. O A. A type I error is the mistake of failing to reject the null hypothesis when the null hypothesis is actually true. A type Il error is the mistake of rejecting the null hypothesis when the null hypothesis is actually false. O B. A type I error is the mistake of rejecting the null hypothesis when the null hypothesis is actually false. A type II error is the mistake of failing to reject the null hypothesis when the null hypothesis is actually true. OC. A type I error is the mistake of rejecting the null hypothesis when the null hypothesis is actually true. A type II error is the mistake of failing to reject the null hypothesis when the null hypothesis is actually false. O D. A type I error is the mistake of failing to reject the null hypothesis when the null hypothesis is actually false. A type II error is the mistake of rejecting the null hypothesis when the null hypothesis is actually true.

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