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# SPSS WORKSHEET 4: (ANCOVA)

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SPSS Worksheet 4: (ANCOVA)

Instructions: Lesson 27 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.

H01: There is no significant difference among the depression scores of students who receive Journal and Counseling therapy, Journal therapy only, or Counseling therapy only, while controlling for pre-test depression scores.
Assumptions
Outliers: Create a Box and Whisker plot for each group.

Insert Graph or Table Here

Fill in the blanks:
Group (Pre-Test):

Outliers (Item #)

Are there any outliers?

Journal and Counseling

Journal only

Counseling only

Group (Post-Test):

Outliers (Item #)

Are there any outliers?

Journal and Counseling

Journal only

Counseling only

< Note: Remove any outliers from the dataset before continuing.>

Assumption of Normality: Run a normality test for each group. Insert Tests of Normality table below:

Insert Graph or Table Here
Fill in the blanks:
Should you use a Shapiro-Wilks or Kolmogorov-Smirnov test? Why?

Groups (Pre-Test)

Significance

Is the assumption of normality met?

Journal and Counseling

Journal only

Counseling only

Groups (Post-Test)

Significance

Is the assumption of normality met?

Journal and Counseling

Journal only

Counseling only

Assumption of Linearity: Hint: Run a series of scatter plots between the pre-test variable and post-test variable for each group. Begin by going to Data > Split File (see lesson 15, p. 64), and then make the plots. Add line of fit. See Warner p. 168- 172. After making the scatterplots, go to Data > Split File > RESET before continuing with the analysis.
Insert Graph or Table Here

Fill in the blanks:
Variables

Is the assumption of linearity met?

Journal & Counseling (Pre)  Journal & Counseling (Post)

Journal only (Pre)  Journal only (Post)

Counseling only (Pre)  Counseling only (Post)

Assumption of Bivariate Normal Distribution: Hint: Run a series of scatter plots between the pre-test variable and post-test variable for each group (Same as above). Look for the classic “cigar shape.”  See Warner p. 168- 172.

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