Part 1
Open the divorce.sav data file and run the one-way ANOVA to answer the following question:
What are the effects of marital status on life satisfaction?
1. State the independent and dependent variables.
2. State the null and alternate hypotheses.
3. Run the appropriate analysis using SPSS (Hint: Use the General Linear Models and Univariate Procedure. Select Estimates of Effect Size under the Options tab).
4. What are the mean and standard deviation for each of the levels of the IV?
5. Report the appropriate F statistic, degrees of freedom, p value, and eta squared (η2).
6. What is your decision regarding the null hypothesis (i.e., did you reject or fail to reject the null)? Explain your decision (1 sentence)
7. Write up a sample results section using APA style.
Part 2
Use the goggles.sav data to run a two-way ANOVA. Consider the following example and then answer the subsequent questions:
Derived from Field (2005), an anthropologist was interested in the effects of alcohol on mate selection at night-clubs. Her rationale was that after alcohol had been consumed, subjective perception of physical attractiveness would become more inaccurate. She was also interested in whether this effect was different for men and women. She picked 48 students: 24 male and 24 female. She then took groups of eight participants to a night-club and gave them either a non-alcoholic lager, 2 pints of strong lager, or 4 pints of strong lager. At the end of the evening she took a photograph of the person that the participant was chatting up. She then got a pool of independent judges to assess the attractiveness of the person in each photograph (out of 100).
1. State the independent variables and the dependent variable.
2. State the null and alternate hypotheses.
3. Run the appropriate analysis and include the Levene’s (Homogeneity of Variance) test and the test of Between-Subjects Effects (Cut and Paste Levene’s Test Output Below – Explain the meaning of this test).
Tests of Between-Subjects Effects (Include Data from Output in the Figure Provided Below)
Source
Df
Mean Square
F
Sig.
Gender
Alcohol
Gender*alcohol
4. Report the mean and standard deviation for each level of the IV (Cut and Paste Output).
5. What is your decision concerning the null hypothesis (i.e., did you reject or fail to reject the null)? Explain your response.
6. Post the Estimated Marginal Means of Attractiveness of Data.
7. Using APA style, write up a sample results section.
Assignment 5: Evaluation Form
Characteristics Assessed
Excellent
Adequate
Insufficient
Part 1.
One-Way ANOVA
5
4
0-3
Part 2.
Two-Way ANOVA
10
8-9
0-7
Total Points Earned: ____ / 15 Points Possible
Assignment 6: Non-Parametrics
Part 1
Chi-Square Test of Association (Independence)
A school system is concerned about the low graduation rate among their high school students. The superintendent assigned a task force to research possible reasons that could explain the low graduation rate. The task force decided to conduct a preliminary literature review about current graduation rate research. The literature review signaled that among several key factors that are related to completion of high school is the development and execution of a school guidance intervention plan. The task force decided to investigate if such is the case in the high school with the highest dropout rate in their district. The following data was collected:
Valenti High School Data
Guidance Intervention Plan
Students obtaining a high school diploma
No
Yes
No
577
46
Yes
381
492
In order to run the chi-square test of association (aka, chi-square test of independence), open the file named: assign 6 prob 1 data.sav
· Under View > Value labels you can toggle between the variable category label (no, yes) or the dummy codes (numeric representation) for the category label (0 = no, 1 = yes)
· Make sure you review both the “Data view” and “Variable view” so you understand the variable types and other properties – and how the variables were created and entered.
· Go to Analyze > Descriptive statistics > Frequencies, and move the two variables to the “Variables” box, then click “ok”
· This gives you the frequencies and percents of each of the variables
· To run the chi-square of association test, go to Analyze > Descriptive statistics > Crosstabs, then move High School Diploma (HSD) to the “Row” box, and Guidance Intervention Plan (GIP) to the “Column” box
· Select “Statistics” then select the “Chi square” and “Phi and Cramer’s V” boxes
· Click “Continue”
· Select “Cells” then select “Observed” and “Expected” under “Counts” (“Round cell counts” is selected by default)
· Click “Continue” then “ok”
Use the output for Questions 1-3:
You were asked to analyze the data and present the findings in the upcoming school board meeting. Your report must include the following:
1. A short explanation about the following (cut and past the output into your Word document):
a. Chi-Square Test of Association.
b. The Case Processing Summary table .
c. Cross tabulation table .
d. Chi-square Tests table.
e. Clustered Bar Chart.
2. Write down the value of the Pearson chi-square and its associated tail probability (p-value). Is it significant? (complete an APA style write-up)
3. In terms of the experimental hypothesis, what has this test shown?
Part 2
Chi-Square Goodness of Fit Test
Following are the cumulative number of AIDS cases reported for Neptune County through December 31, 2008, broken down by ethnicity:
Ethnicity
Actual Number of AIDS Cases
White
751
Hispanic
225
African-American
100
Asian, Pacific Islander
36
Native American
5
Total = 1117
Ethnicity
Percentage of total county population
Expected cases by population
1 = White
51
570
2 = Hispanic
23
257
3 = African American
4
45
4 = Asian, Pacific Islander
21
235
5 = Native American
1.0
10
Total = 100%
Total = 1117
In order to run the chi-square goodness of fit test, open the file named: assign 6 prob 2 data.sav
· Under View > Value labels you can toggle between the variable category label (White, Hispanic, African American, Asian Pacific Islander, Native American) or the dummy codes (numeric representation) for the category label (1 = White, 2 = Hispanic, 3 = African American, 4 = Asian Pacific Islander, 5 = Native American). For this test, we want to compares the observed (actual) AIDS cases to the expected cases (frequencies, based on county population).
· Go to Analyze > Nonparametric tests > Chi square
· Move the AIDS variable to the “Test variable list” box
· Using the “Expected cases by population” numbers that correspond to each ethnic group in the table above, under “Expected values” select, “Values” then add the 5 population percentages that correspond with the frequency in the sample, using “Add” for each (570 > Add, 257 > Add, 45 > Add, 235 > Add, 10 > Add)
· Select “Descriptive” > Continue under “Options”
· Click “ok”
You will use the output for Questions 1-5:
Determine whether the make-up of AIDS cases follows the ethnicity of the general population of Neptune County. State the following:
1. Null Hypothesis
2. Decision
3. Reason for the Decision (paste the output that includes the statistical significance into Word)
4. Does it appear that the pattern of AIDS cases in Neptune County corresponds to the distribution of ethnic groups in this county? Why or why not?
5. You are asked to report your findings along with recommendations for prioritizing interventions by ethnic group to the County Health Commission. Write a one paragraph handout summarizing the findings and your recommendations. Also include the results, in APA style.
Assignment 6: Evaluation Form
Characteristics Assessed
Excellent
Adequate
Insufficient
Part 1.
Chi-Square Test of Association
5
4
0-3
Part 2.
Chi-Square Goodness of Fit Test
10
8-9
0-7
Total Points Earned: ____ / 15 Points Possible
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