Computing T-tests and ANOVAS.

Instructions

t-tests:

• Run your independent samples t-test examining the differences between men and women in much hurt they reported experiencing immediately after a breakup occurred. (columns A & B in the dataset)
• Summary paragraph: explain the result of your t-test in a paragraph while addressing the following information:
• Was the t-test significant or not significant? And what does that mean for a t-test
• What were the group means for each group? Include them as you explain what you found.
• Create a graph or chart to help visualize this data and paste it in the same worksheet.
• Reference your graph in your summary.

Oneway ANOVA:

• Run a oneway ANOVA (single factor) examining how the medium used to enact a breakup (in-person/phone call/email/text message) impacts the current levels of happiness in regard to the breakup. (columns C-F).
• paste your output in the same workbook to the right of your t-test output
• If ANOVA is significant, Run a post hoc tests.
• calculate the effect size for the anova (equation: Between group SS/Total SS)
• Summary paragraph: Explain the results of the anova in a short paragraph while addressing the following:
• Was it significant or not significant?
• If it was significant, what did the post hoc results tell you?
• Make sure to explain which pairs of groups differed significantly while including the group means as you explain the results
• What was the effect size? What does that mean?
• Create a graph or chart to help visualize the data and make reference to it in your write up.
• Submit your assignment as an excel file.
• Steps for running an independent samples t-test in Excel:
• Make sure that
• Choose t-test: Two sample assuming equal variances from Data Analysis tab
• Click the labels box so they will be included
• Enter the range of variable 1 (group 1s scores) and range of variable 2 (group 2s scores)
• Choose a cell for the output table to go
• Steps for running oneway ANOVA in Excel:

1. Format columns for IV groups with their DVscores (if not done already)
2. Choose Anova: Single Factor from the Data Analysis tab
3. Click box for labels in first row
4. Grouping: make sure columns is selected
5. Input range: Highlight the data in the columns with your different groups scores (including headings)
6. Output options: select the output range option and select the cell you want the results table to show up
7. Examine table to determine if F-test/ANOVA was significant.
8. If significant, continue with the following steps:

• Post hoc results if ANOVA is significant (if ANOVA was not significant, dont proceed)

1. Calculate Number of pairwise comparisons needed using this formula: k*(k-1)/2
2. K = # of groups
3. Run “ind samples t-tests for unequal variances” from data analysis tab for each pair of groups
4. Example: group 1-group 2, group 1-group3, and group2-group3 = 3 tests
5. Keep output range to same worksheet and paste output tables near each other (nearby cells)
6. (Should end up with a t-test table for each pair of groups)
7. Next, Calculate Bonferroni to adjust the alpha level for running multiple of the same test (increases our chance of committing Type 1 error)
8. Formula: Divide .05 by the number of t-tests (pairwise comparisons) you did
9. Compare the Bonferroni corrected alpha value to the p value (2 tailed) for each t-test,
10. example: if you ran 3 t-tests to compare your groups, then you would divide .05/3 =.02
11. If the p value (two-tailed) of each ind samples t-test is equal to or less than corrected alpha, that pair of groups are significantly different from each other

• Please make sure to read chapters 12 and 14 from the textbook as well.

Grading Criteria (20pts)

Grading Rubric

• Content (20pts)
• Content of t-test (10pts)
• Was the test run with the correct variables? (1pt)
• Was the significance of the test addressed correctly? (2pt)
• Did they create a graph or chart to help explain results? (2pts)
• t-test Summary paragraph:
• Did the results get explained while including the group means (4pts)
• Was the effect size mentioned? (1pts)
• ANOVA analyses (5pts)
• Correct variables were used to compute results (1pt)
• Post hoc tests were computed if F test was significant (1pts)
• effect size was computed (1pt)
• A graph was created to help explain results (1pt)
• ANOVA summary paragraph (5pts):
• Significance of the anova addressed? (1pt)
• post hoc results used to describe significant pairwise differences? (2pts)
• accurately described group differences found (while including group means) (1pt)
• effect size mentioned? (1pt)

Submission details:

• Assignment is submitted as an Excel file