SPSS Worksheet 4 Resubmit needed tomorrow! 11-11-17 @ 12 noon

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Week 4 Worksheet
SPSS Week 4: ANOVA
This week, you will complete two exercises related to One-Way, Two-Way, and Repeated-Measures ANOVA tests.
Part I:
Download the data set divorce-studentversion.sav from this week’s resources. Review both the Data View and the Variable View to obtain a general understanding of the data.
In this study, the researcher is interested in studying life satisfaction as the dependent variable. First as a one-way ANOVA, then as a multiple (factorial) ANOVA, the researcher will ask questions related to differences among fixed groups. In this data set, the variables (factors) of interest are life satisfaction, current family income, and gender. 
In all of the analyses conducted in this assignment, be sure to select the option that provides a measure of effect size (Eta) and the homogeneity test (Levene’s test).
Based on experience and knowledge of the literature, the researcher first wants to measure how different income levels impact life satisfaction. Using General Linear Model/univariate, conduct the analysis used to assess the differences among income levels on life satisfaction. Then, conduct the Tukey HSD post hoc comparison test. (As you can see from the post hoc window,there is a large array of post hoc tests available; as you read the literature in your specialization, see if there is a preferred post hoc test. If in your research you need to conduct a post hoc test, the selected test might be influenced by the literature in your area. Tukey is used here simply as an example.)
Using General Linear Model/univariate, analyze the differences between the genders when using life satisfaction as the dependent variable.
Using the General Linear Model/univariate, conduct a two-way ANOVA analyzing both gender and family income levels as related to life satisfaction.
Using scholarly writing and proper APA format, please complete, and then submit the following:
Present two tables:
Table 1 should show the results of a one-way ANOVA based on current family income, including Eta.
Table 2 should show the results of a two-way ANOVA based on both current family income and gender, including Eta.
Provide a narrative discussion of both tables. Include Eta, the Levene test, and the observed change in the F-value of current family income when moving from a one-way to a two-way analysis.
Identify, and then explain the information the researcher gained from the Tukey post hoc test.
Include an appendix containing all SPSS output (copied and pasted) for the items above.
Part 2:
Download the data set grades.sav from this week’s resources. Review both the Data View and the Variable View to obtain a general understanding of the data.
Over time, with instruction in between, each student completed a quiz five times. The quiz scores or the measurement of student achievement over time would serve as the dependent variable while instruction would serve as the independent variable/treatment/factor.
Using General Linear Model/repeated measures, conduct a Repeated Measures ANOVA to analyze the influence of repeating the quiz over time on the quiz scores. Include descriptive statistics as an option.
Using scholarly writing and proper APA format, please complete, and then submit the following:
Present two tables. After reviewing the material in the text, decide the most important output to include in the two tables you will present.
Provide a narrative discussion of the tables, including a discussion of SPHERICITY.
Include an appendix that contains all SPSS output (copied and pasted) for the items above.
Reporting Statistics in APA Style
Dr. Jeffrey Kahn, Illinois State University
The following examples illustrate how to report statistics in the text of a research report. You will note that significance levels in journal articles–especially in tables–are often reported as either “p > .05,” “p< .05,” “p < .01,” or “p < .001.” APA style dictates reporting the exact p value within the text of a manuscript (unless the p value is less than .001).
Please pay attention to issues of italics and spacing. APA style is very precise about these. Also, with the exception of some p values, most statistics should be rounded to two decimal places.
Mean and Standard Deviation are most clearly presented in parentheses:
The sample as a whole was relatively young (M = 19.22, SD = 3.45).The average age of students was 19.22 years (SD = 3.45).
Percentages are also most clearly displayed in parentheses with no decimal places:
Nearly half (49%) of the sample was married.
Chi-Square statistics are reported with degrees of freedom and sample size in parentheses, the Pearson chi-square value (rounded to two decimal places), and the significance level:
The percentage of participants that were married did not differ by gender, c2(1, N = 90) = 0.89, p = .35.
T Tests are reported like chi-squares, but only the degrees of freedom are in parentheses. Following that, report the t statistic (rounded to two decimal places) and the significance level.
There was a significant effect for gender, t(54) = 5.43, p < .001, with men receiving higher scores than women.
ANOVAs (both one-way and two-way) are reported like the t test, but there are two degrees-of-freedom numbers to report. First report the between-groups degrees of freedom, then report the within-groups degrees of freedom (separated by a comma). After that report the F statistic (rounded off to two decimal places) and the significance level.
There was a significant main effect for treatment, F(1, 145) = 5.43, p = .02, and a significant interaction, F(2, 145) = 3.24, p = .04.
Correlations are reported with the degrees of freedom (which is N-2) in parentheses and the significance level:
The two variables were strongly correlated, r(55) = .49, p < .01.
Regression results are often best presented in a table. APA doesn’t say much about how to report regression results in the text, but if you would like to report the regression in the text of your Results section, you should at least present the unstandardized or standardized slope (beta), whichever is more interpretable given the data, along with the t-test and the corresponding significance level. (Degrees of freedom for the t-test is N-k-1 where k equals the number of predictor variables.) It is also customary to report the percentage of variance explained along with the corresponding F test.
Social support significantly predicted depression scores, b = -.34, t(225) = 6.53, p < .001. Social support also explained a significant proportion of variance in depression scores, R2 = .12, F(1, 225) = 42.64, p < .001.
Tables are useful if you find that a paragraph has almost as many numbers as words. If you do use a table, do not also report the same information in the text. It’s either one or the other.
Based on:
American Psychological Association. (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC: Author. 
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