Hypothesis Testing Review

The math teacher for an Introduction to Statistics course wants to compare a new textbook to the old one. He takes a random sample of 42 people from each of two classes. The class using the new book got an average of 88 on the final exam given and had a standard deviation of 3 points. The class using the old book had an average of 90 with a standard deviation of 2 points. Is there convincing evidence of a difference in student performance on the test between the two groups? What kind of test is appropriate?

• One Proportion (1-PropZtest)

• Difference of Proportions (2-PropZtest)

• One Mean (ttest)

• Mean Difference (t-test)

• Difference of Means (2-SamptTest)

The math teacher for an Introduction to Statistics course wants to compare a new textbook to the old one. He takes a random sample of 42 people from each of two classes. The class using the new book got an average of 88 on the final exam given and had a standard deviation of 3 points. The class using the old book had an average of 90 with a standard deviation of 2 points. Is there convincing evidence of a difference in student performance on the test between the two groups? What are the null and alternative hypotheses?

The math teacher for an Introduction to Statistics course wants to compare a new textbook to the old one. He takes a random sample of 42 people from each of two classes. The class using the new book got an average of 88 on the final exam given and had a standard deviation of 3 points. The class using the old book had an average of 90 with a standard deviation of 2 points. Is there convincing evidence of a difference in student performance on the test between the two groups? What is the p-value? (to nearest FOUR decimal places)

The math teacher for an Introduction to Statistics course wants to compare a new textbook to the old one. He takes a random sample of 42 people from each of two classes. The class using the new book got an average of 88 on the final exam given and had a standard deviation of 3 points. The class using the old book had an average of 90 with a standard deviation of 2 points. Is there convincing evidence of a difference in student performance on the test between the two groups? What is your conclusion?

• Reject the null. There is strong evidence of a difference in student performance.

• Fail to reject the null. There is not strong evidence of difference in student performance.

• Reject the null. There is not strong evidence of a difference in student performance.

• Fail to reject the null. There is strong evidence of a difference in student performance.

TThe math teacher for an Introduction to Statistics course wants to compare a new textbook to the old one. He takes a random sample of 42 people from each of two classes. The class using the new book got an average of 88 on the final exam given and had a standard deviation of 3 points. The class using the old book had an average of 90 with a standard deviation of 2 points. Is there convincing evidence of a difference in student performance on the test between the two groups? Describe a Type I Error.

• Say there is a difference in performance between students using the different texts but there isn't.

• Say there is a difference in performance between students using the different texts and there is.

• Say there is not a difference in performance between students using the different texts but there is.

• Say there is not a difference in performance between students using the different texts and there isn't.

A production line produces rulers that are supposed to be 12 inches long. A sample of 49 of the rulers had a mean of 12.1 and a standard deviation of 0.5 inches. The quality control specialist responsible for the production line decides to do a hypothesis test to determine whether the production line is producing rulers that are 12 inches long or not. What kind of test is appropriate?

• One Proportion (1-PropZtest)

• Difference of Proportions (2-PropZtest)

• One Mean (ttest)

• Mean Difference (t-test)

• Difference of Means (2-SamptTest)

A production line produces rulers that are supposed to be 12 inches long. A sample of 49 of the rulers had a mean of 12.1 and a standard deviation of 0.5 inches. The quality control specialist responsible for the production line decides to do a hypothesis test to determine whether the production line is producing rulers that are 12 inches long or not. What are the null and alternative hypotheses?

A production line produces rulers that are supposed to be 12 inches long. A sample of 49 of the rulers had a mean of 12.1 and a standard deviation of 0.5 inches. The quality control specialist responsible for the production line decides to do a hypothesis test to determine whether the production line is producing rulers that are 12 inches long or not. What is the p-value? (to the nearest TWO decimal places)

A production line produces rulers that are supposed to be 12 inches long. A sample of 49 of the rulers had a mean of 12.1 and a standard deviation of 0.5 inches. The quality control specialist responsible for the production line decides to do a hypothesis test to determine whether the production line is producing rulers that are 12 inches long or not. What is the conclusion at the 0.05 level of significance?

• Reject the null. There is strong evidence the rulers are not the correct length.

• Reject the null. There is not strong evidence the rulers are not the correct length.

• Fail to reject the null. There is strong evidence the rulers are not the correct length.

• Fail to reject the null. There is not strong evidence the rulers are not the correct length.

A production line produces rulers that are supposed to be 12 inches long. A sample of 49 of the rulers had a mean of 12.1 and a standard deviation of 0.5 inches. The quality control specialist responsible for the production line decides to do a hypothesis test to determine whether the production line is producing rulers that are 12 inches long or not. Which of the following would increase the power of the test? (Select all that apply).

• Increase the sample size.

• Decrease the probability of a Type II error.

• Increase the probability of a Type I error.

• Increase the probability of a Type II error.