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A psychology instructor at a large university teaches statistics. There are 22 students in the class, and he has broken them into two groups. Each

A psychology instructor at a large university teaches statistics. There are 22 students in the class, and he has broken them into two groups. Each group has a different graduate assistant who is responsible for running separate breakout lecture and lab sections of the course. One graduate assistant (GA) has lots of experience teaching, while the other has more limited experience. The instructor wants to check for comparable learning across the two GAs, hoping students receive similar experiences (i.e., to find no difference). The data below are the scores (out of 100) of the students on the first midterm. Use it to test whether there is a difference between the groups.

Group 1 (less experienced GA) Group 2 (more experienced GA)
60 70
65 85
69 72
58 83
57 81
59 69
52 65
72 75
70 79
65 71
75 80

  1. In this specific scenario, what is the independent variable? Is it between or within subjects? How many levels does it have, and what are they?

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  1. In this specific scenario, what is the dependent variable? What is its scale of measurement?

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  1. Paste all relevant statistical output in the space provided below:

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Please explain how to make a graph in SPSS and paste it in the space provided below:

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This includes a full write-up to include a complete statistical notation as shown in the weekly presentations. The write-up also needs interpretation. If significant, state how. If it is not significant, what does that mean in layman's terms?

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  1. Using information from this scenario, determine the degrees of freedom and whether this is a one- or two-tailed test. Use the Appendix in your e-book to find the critical value. Do not round - provide the exact critical value below. Label it "critical value". Also provide the "obtained value" from your SPSS (and label it as such).

Compare the critical and obtained values - does the critical value exceed the obtained value? What does this mean in regards to the null hypothesis (would you reject or fail to reject the null hypothesis)?

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