Dr. Knobel wanted to explore the differences between treatment A and treatment B
ID: 3057001 • Letter: D
Question
Dr. Knobel wanted to explore the differences between treatment A and treatment B and so she randomly assigned 20 participants to receive treatment A and the other 20 received treatment B. What kind of t-test should Dr. Knobel use to test this difference?
Question 1 options:
Between-subjects design
Within subjects design
One sample t-test
In the PenCast, all of the terms were used to describe the t-test appropriate for the scenario above
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Question 2 (1 point)
Dr. Johnson wanted to explore the impact of treatment on a group of depressed patients. He measured the patients’ level of depression, gave them all a 12 week course of treatment and then measured their levels of depression again after the treatment had completed. What t-test should he use to explore the difference between the initial level of depression and the post-treatment level of depression?
Question 2 options:
Between-subjects design t-test
Independent samples t-test
Two-sample t-test
In the PenCast, all of the terms were used to describe the t-test appropriate for the scenario above
Within subjects t-test
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Question 3 (1 point)
The standard null hypothesis for a non-directional t-test for independent samples is
Question 3 options:
population mean of group 1 is greater than population mean of group 2
population mean of group 2 is greater than population mean of group 1
population mean of group 1 minus population mean of group 2 = 0
sample mean of group 1 minus sample mean of group 2 = 0
sample mean of group 1 minus sample mean of group 2 does not equal 0
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Between-subjects design
Within subjects design
One sample t-test
In the PenCast, all of the terms were used to describe the t-test appropriate for the scenario above
Explanation / Answer
1. Answer: Between-subjects design
Reason: As test is conducted on results of different samples.
2. Answer: Within subjects t-test
Reason: As the test is conducted on same sample but at different times.
3. Answer: population mean of group 1 minus population mean of group 2 = 0
Reason: Null hypothesis always contains equality and always talks about population parameters.
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