Suppose a statistics teacher wants to evaluate whether her students who received online lectures did worse on average on exams than students who received in-person instruction. She collects the list of exam grades for all students in the online section of her course (110 students) and the list of exam grades for all students in the in-person section of her course (115 different students) and compute a two-sample z test using the average scores. She makes histograms of both sets of scores separately and notes that both are skewed left. How would you critique carrying out a test using the two-sample z test in this situation? Choose the best response. Group of answer choices The histograms of the scores do not follow the normal curve, so the z test is not appropriate. There is dependence between the two samples. There is no valid box model here with random sampling, since the teacher has the data for all the students. The sample sizes are different, so you can't compute the test statistic.

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Suppose a statistics teacher wants to evaluate whether her students who received online lectures did worse on average on exams than students who received in-person instruction. She collects the list of exam grades for all students in the online section of her course (110 students) and the list of exam grades for all students in the in-person section of her course (115 different students) and compute a two-sample z test using the average scores. She makes histograms of both sets of scores separately and notes that both are skewed left.

How would you critique carrying out a test using the two-sample z test in this situation? Choose the best response.

Group of answer choices
The histograms of the scores do not follow the normal curve, so the z test is not appropriate.
There is dependence between the two samples.
There is no valid box model here with random sampling, since the teacher has the data for all the students.
The sample sizes are different, so you can't compute the test statistic.
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