PS390 Statistical Reasoning in Psychology
click here for more information on this paper
Directions: Be sure to save an electronic copy of your answer before submitting it to Ashworth College for grading. Unless otherwise stated, answer in complete sentences, and be sure to use correct English, spelling, and grammar. Sources must be cited in APA format. Your response should be four (4) double‐spaced pages; refer to the “Format Requirementsʺ page for specific format requirements.
StatCrunch tutorial videos are available at http://www.youtube.com/view_play_list?p=BE055F65E43B4973.
- (25 points) A sports psychologist gave a questionnaire about healthy eating habits to randomly selected professional athletes. The results are displayed below. Using the .05 significance level, is there a difference in healthy eating habits among professionals in the three sports?
Baseball Players Basketball Players Football Players
32 27 27
27 36 23
26 25 26
35 30 20
- Make a graph for the data set.
- Use the five steps of hypothesis testing (report results in APA format).
- Figure the effect size of this study.
- Conduct a planned contrast for Baseball versus Football players (using Tukey’s HSD).
- (25 points) A researcher is interested in the effects of sleep deprivation and caffeine intake on mood. Participants were randomly assigned to a sleep condition (normal or deprived) and a caffeine condition (0 cups, 2 cups, or 4 cups). After the manipulations, mood was measured (such that higher numbers indicated better mood). The results were as follows:
Normal Condition Deprived Condition
0 cups 2 cups 4 cups 0 cups 2 cups 4 cups
16 18 18 0 5 6
17 20 17 6 4 8
20 20 17 3 4 6
19 19 17 2 2 7
18 18 16 4 5 8
Analyze these data using a factorial analysis of variance and including R2 for each effect.
- (25 points) A researcher was interested in whether college GPA (X) would predict starting salary after college (Y). (For simplicity, salary was converted to a 100-point scale.) The participants’ scores were:
M = 2.75 M = 50
- Report the correlation and linear prediction equation.
- Make a graph with the regression line.