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
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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 |
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- A Type II error is defined as a. rejecting a null hypothesis when it is in fact true b. failing to reject a false null hypothesis c. rejecting a false null hypothesis d. failing to reject a true null hypothesisA researcher has rejected the null hypothesis when in reality, the null hypothesis is false. What type of error has she committed, if any? Type II error Digit reversal error Type I error No error; Correct decisionA Type I error occurs if you reject the null hypothesis when in fact it is true. a.)True b.)False
- Which 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 hypothesisWhich of the following is an accurate definition of a Type II error? Group of answer choices rejecting a false null hypothesis rejecting a true null hypothesis failing to reject a false null hypothesis failing to reject a true null hypothesisThe error of rejecting a true null hypothesis is a. a Type I error b. a Type II error c. can be either a or b, depending on the situation d. committed when not enough information is available
- Which 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.When a null hypothesis can be rejected by an extreme result in one direction only, a two-tail test is appropriate. a) True b) FalseA type I error could be committed even if the null hypothesis is false True False
- When is a researcher at risk of making a type 2 error? whenever H0 is rejected whenever H1 is rejected whenever H0 fails to reject the risk of a type 2 is independent of the decision from a hypothesis testFor the following null and alternative hypothesis describe the scenario of an instructor making a Type I Error Ho: A student is not cheating on an Exam H1: A student is cheating on an ExamMy lawn needs mowing , but i do not want to mow if its going to start raining while I'm in the middle of the job. So i am looking at the sky evaluating the weather, using the null hypothesis: "It will rain within the next two hours". In this situation , what would a type I error be?