SPSS Worksheet 3: (Two-Way ANOVA)
This worksheet was developed by Dr. Kurt Michael of Liberty University © 2015
Name:
Instructions: Lesson 26 Exercise File 2 is located at the end of the chapter under the heading Exercises in your Green and Salkind textbook. Complete the exercise and then complete the worksheet below by filling in the blanks and answering the questions.
Note: The two-way ANOVA looks at three null hypotheses at one time.
H01: There is no significant difference among the amount of time fathers play with their children with no disability, a physical disability, or an intellectual disability.
H02: There is no significant difference between the amount of time fathers play with their male or female children.
H03: There is no significant interaction among the amount of time fathers play with their male or female children with no disability, a physical disability, or an intellectual disability.
Assumptions
Outliers: Create a Box and Whisker plot for each group. Hint: Go to Graph > Legacy Dialog > Boxplot and use the Cluster function. See page 184 in the Salkind and Green textbook for more information on how to display results.
Insert Graph or Table Here
Fill in the blanks:
Group |
Outliers (Item #) |
Are there any outliers?
|
Male Typically |
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Male Physical |
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Male Mental |
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Female Typically |
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Female Physical |
|
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Female Mental |
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< Note: Remove any outliers from the dataset before continuing.>
Assumption of Normality: Run a normality test each group. Hint: Begin by going to Data > Split File > Organize output by groups (see lesson 15, p. 64), then run Analyze > Descriptive > Explore (see lesson 40, p. 327). Insert six Tests of Normality tables below:
Insert Graph or Table Here
Fill in the blanks:
Should you use a Shapiro-Wilks or Kolmogorov-Smirnov test? Why?
Groups |
Significance |
Is the assumption of normality met? |
Male Typically |
|
|
Male Physical |
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Male Mental |
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Female Typically |
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Female Physical |
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Female Mental |
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Assumption of Equal Variance: Insert Levene’s Test of Equality of Error Variancesa table(s) below. Hint: Begin by going to Data > Split File > RESET > then run the Analyze.
Insert Graph or Table Here
Fill in the blanks:
Significance |
Is the assumption of equal variance met? |
|
|
Results
Insert Tests of Between-Subjects Effects table(s) below:
Insert Graph or Table Here
Differences among disabilities
Fill in the blanks:
Results for Disability: |
Value |
d.f. between Groups |
|
d.f. within Groups |
|
F-statistic |
|
F-critical (See Appendix C in Warner) |
|
p– value |
|
Partial Eta Squared |
|
Is the F– statistic greater than F-critical?
Is the p– value less than .05?
Should you reject or fail to reject the null?
What is the effect size small, medium, or large (See Table 5.2 in Warner, p. 208)?
Should you run post hoc analysis?
If so, between which groups do the differences exist?
Differences between genders
Fill in the blanks:
Results for Gender: |
Value |
d.f. between Groups |
|
d.f. within Groups |
|
F-statistic |
|
F-critical (See Appendix C in Warner) |
|
p– value |
|
Partial Eta Squared |
|
Is the F– statistic greater than F-critical?
Is the p– value less than .05?
Should you reject or fail to reject the null?
What is the effect size small, medium, or large (See Table 5.2 in Warner, p. 208)?
Should you run post hoc analysis? Hint: There are only two groups (Male and Females).
Interaction among groups
Fill in the blanks:
Results for Interaction: |
Value |
d.f. between Groups |
|
d.f. within Groups |
|
F-statistic |
|
F-critical (See Appendix C in Warner) |
|
p– value |
|
Partial Eta Squared |
|
Is the F– statistic greater than F-critical?
Is the p– value less than .05?
Should you reject or fail to reject the null?
What is the effect size small, medium, or large (See Table 5.2 in Warner, p. 208)?
Descriptive Statistics
Fill in the blanks:
Groups |
Mean |
S.D. |
Male Typically |
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|
Male Physical |
|
|
Male Mental |
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Female Typically |
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Female Physical |
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Female Mental |
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