Spss worksheet 3: (two-way anova)

 

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

 

 

 

Male Physical

 

 

 

Male Mental

 

 

 

Female Typically

 

 

 

Female Physical

 

 

 

Female Mental

 

 

 

 

 

 

< 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

 

 

 

Male Mental

 

 

 

Female Typically

 

 

 

Female Physical

 

 

 

Female Mental

 

 

 

 

 

 

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

 

 

 

Male Physical

 

 

 

Male Mental

 

 

 

Female Typically

 

 

 

Female Physical

 

 

 

Female Mental

 

 

 

 

 

 

 

 

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