Which of the following is an example of a Type 1 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.

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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 hypothesis

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 significance

You complete a hypothesis test using α = .05, and based on the evidence from the sample, your decision is to fail to reject the null hypothesis. If the treatment actually does NOT have an effect, which of the following is true?   Group of answer choices   You have made a Type II error. You have made the correct decision. You might have made a Type I error, but the probability is only 5% at most. You have made a Type I error.

On Monday, Philip rejected a null hypothesis that was true. On Tuesday, he retained a true null hypothesis. What kind of week is he having? o.k. – he made a Type I error on Monday and a correct decision on Tuesday bad – he is confounded and his power level is too low bad – he made a Type I error on Monday and a Type II error on Tuesday bad – he made a Type II error on Monday and a Type I error on Tuesday

A medical researcher claims that 70% of people pay for prescriptions with private insurance, 25% pay with Medicare, and the remaining pay with personal funds. To evaluate this claim, a random sample of 50 people was taken. The sample had the following results: Private Insurance Medicare Personal 32 10 8 What is the null hypothesis for the test? Enter the null hypothesis in the first blank. You do NOT need to enter the alternative hypothesis. Calculate the test statistic for the test and enter it in the second blank. Round your final answer to three decimals. Find the critical value cutoff for the rejection region and enter it in the third blank. Use alpha = 0.005.

Which of the following statements are TRUE? I. Increasing the significance level of a test will increase the chance of erroneously rejecting a true null hypothesis. II. Increasing the significance level of a test will increase the chance of erroneously failing to reject a false null hypothesis. Only statement I is true. Neither statement is true. Only statement II is true. Both statements are true.

Retaining a false null hypothesis, which type of error it is?