.Probability of accept a hypothesis when it is wrong is known as O a. Confidence level O b. Type II error O c. Significance level O d. Type I error
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- Suppose a hypothesis test was performed with a level of significance of 0.05. Then if the null hypothesis is actually true, then there is a 5% chance that the researcher will end up rejecting the null hypothesis in error. True FalseTest the claim that the mean GPA of night students is larger than 2.4 at the 0.025 significance level. The null and alternative hypothesis would be: Ho p≥ 0.6 Ho:μ ≤ 2.4 Ho:p ≤ 0.6 H₁ p 2.4 H₁:p > 0.6 Ho:. :p= 0.6 Ho:} > 2.4 Ho: = 2.4 H₁:p‡ 0.6 H₁:μ< 2.4 H₁:µ ‡ 2.4 The test is: two-tailed left-tailed right-tailed Based on a sample of 60 people, the sample mean GPA was 2.41 with a standard deviation of 0.02 The p-value is: (to 2 decimals) Based on this we: O Fail to reject the null hypothesis O Reject the null hypothesisA hypothesis test uses a significance level of 5%. The Power of the Test is 0.90. Which of these statements are True? I. The Probability of incorrectly rejecting the Null is 0.05. II. The probability of incorrectly accepting the Null is 0.10. A. I only. B. II only. C. I. & II. D. None of them. А. А В. В С. С D. D
- What is the power of a test? Select all that apply. a.The probability that a significance test will pick up on the fact that the true value is different from the null. b.The probability of incorrectly rejecting the null when it's true. c.The probability of incorrectly failing to reject the null when it's false. d.The probability of correctly rejecting the null when the null is false. e.The probability of avoiding a type 2 errorIf an experimenter realizes that the consequences of a type one error are severe, then he will most likely set the significance level of the test at 5% or possibly higher if the consequences are particularly troublesome a. true b. falseIn a test of statistical hypotheses, the P-value tells us O the probability of observing a sample mean as we did or something more unusual if the null hypothesis is true. if the null hypothesis is true. if the alternative hypothesis is true. the largest level of significance at which the null hypothesis can be rejected.
- Suppose we know that a confidence interval for a population proportion is (0.105,0.355), with a sample proportion of p̂=0.23. What is the margin of error?In doing a test of statistical significance, you will have made a Type I error if you concludethat there is no difference between means in the population when in fact there is a difference the absence of a difference in the samples is due to chance any difference in the samples is due to chance there is a difference between means in the population when in fact there is no differenceSee attached
- Which one of the following statements is incorrect: A. A type I error consists of rejecting the null hypothesis when it is true B. A type II error consists of accepting the null hypothesis when it is false C. You can control simultaneously both the Type I and Type II error probabilities when the sample size is fixed D. Hypothesis testing and confidence intervals are related concepts1. If the chance for a student passing a class is 50%, then the chance for a student not passing the class can be greater than 50%? true or false 2. 1.30% is not a true probability? true or false 3. Power is 1 minus the probability of making a type I error? true or false 4. Using the same sample data, the margin of error for an 80% confidence interval is bigger than the margin of error for a 90% confidence interval? true or falseSuppose a sample of 9 customers spends an average of $200 with a standard deviation $20 what is a 95% confidence interval for the sample mean. Use the fact that 95% of sample means are within 2.306 standard errors of the sample mean.