Exercise 26 photo.docx Lesson 26 Exercise File 2.sav Question.docx Page 1 of 6 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? Answer: 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? Answer: Is the p- value less than .05? Answer: Should you reject or fail to reject the null? Answer: What is the effect size small, medium, or large (See Table 5.2 in Warner, p. 208)? Answer: Should you run post hoc analysis? Answer: If so, between which groups do the differences exist? ...

1. Exercise 26 photo.docx
Lesson 26 Exercise File 2.sav
Question.docx
Page 1 of 6
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

2. 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

3. 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?
Answer:
Groups
Significance
Is the assumption of normality met?
Male Typically
Male Physical
Male Mental
Female Typically
Female Physical
Female Mental

4. 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

5. F-critical (See Appendix C in Warner)
p- value
Partial Eta Squared
Is the F- statistic greater than F-critical?
Answer:
Is the p- value less than .05?
Answer:
Should you reject or fail to reject the null?
Answer:
What is the effect size small, medium, or large (See Table 5.2 in
Warner, p. 208)?
Answer:
Should you run post hoc analysis?
Answer:
If so, between which groups do the differences exist?
Answer:
Differences between genders

6. 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?
Answer:
Is the p- value less than .05?
Answer:
Should you reject or fail to reject the null?
Answer:
What is the effect size small, medium, or large (See Table 5.2 in

7. Warner, p. 208)?
Answer:
Should you run post hoc analysis? Hint: There are only two
groups (Male and Females).
Answer:
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?
Answer:

8. Is the p- value less than .05?
Answer:
Should you reject or fail to reject the null?
Answer:
What is the effect size small, medium, or large (See Table 5.2 in
Warner, p. 208)?
Answer:
Descriptive Statistics
Fill in the blanks:
Groups
Mean
S.D.
Male Typically
Male Physical
Male Mental
Female Typically
Female Physical

9. Female Mental
14. Suppose a hypertension trial is mounted and 18 participants
are randomly assigned to one of the comparison treatments.
Each participant takes the assigned medication and their
systolic blood pressure (SBP) is recorded after 6 months on the
assigned treatment. The data are as follows.
Standard Treatment
Placebo
New Treatment
124
134
114
111
143
117
133
148
121
125
142
124
128
150
122

10. 115
160
128
Is there a difference in mean SBP among treatments? Run the
Step 1. Set up hypotheses and determine level of significance
H1: Means are not all equal
Step 2. Select the appropriate test statistic. F=MSB/MSE.
Step 3. Set up decision rule.
df1=k-1=3-1=2 and df2=N-k=18-3=15. Reject H0 if F >
3.68.
Step 4. Compute the test statistic.
Standard
Placebo
New Treatment
n1=6
n2=6
n3=6
1= 122.7
2= 146.2

11. 3= 121.0
If we pool all N=18 observations, the overall mean is = 130.0.
We can now compute .
SSB = 6(122.7-130.0)2 + 6(146.2-130.0)2 + 6(121.0-130.0)2
SSB = 2380.4.
Next, .
Standard Treatment
(X – 122.7)
(X – 122.7)2
124
1.3
1.69
111
-11.7
136.89
133
10.3
106.09
125
2.3
5.29
128
5.3

12. 28.09
115
-7.7
59.29
337.34
-1)2 = 337.34.
Placebo
(X – 146.2)
(X – 146.2)2
134
-12.2
148.84
143
-3.2
10.24
148
1.8
3.24
142
-4.2
17.64
150
3.8
14.44
160
13.8
190.44
384.84

13. -2)2 = 384.84.
New Treatment
(X – 121.0)
(X – 121.0)2
114
-7
49
117
-4
16
121
0
0
124
3
9
122
1
1
128
7
49
124
-3)2 = 124.0

14. = 846.18.
We can now construct the ANOVA table.
Source of
Variation
Sums of Squares
SS
Degrees of freedom df
Mean Squares
MS
F
Between Treatments
2380.4
2
1190.2
21.1
Error or Residual
846.2
15
56.4
Total
3226.6
17
Step 5. Conclusion.
We reject H0 because 21.1 > 3.68. We have statistically
in mean systolic blood pressure among treatments.

15. )
X
-
X
(
n
Σ
=
SSB
j
2
j
)
X
-
X
(
Σ
Σ
=
SSE
j
2

16. X
X
Do the following problems using SPSS and provide a copy of
the ANOVA table for each as your answer:
Sullivan pp. 162-168: 14
PLUS the following problems:
1. A manufacturer wants to know which new coffee sells the
best and distributes 3 types (Blue-Label, Green-Label and Red
Label) to 6 of his stores. After letting customers taste the three
types, the number of pounds purchased of each type of coffee on
one day are recorded for the six stores. Perform an ANOVA
using SPSS to determine whether there is a significant
difference in sales.
Blue-Label Green-Label Red-Label
13 1 5
4 1 2
10 2 2
13 2 2
11 2 6
3 4 4
2. Three topical antibiotics are tested to see how quickly they
eliminate a rash in 4 people who have a history of repeated
rashes of this type.
The number of days to eliminate the rash in the 4 people is
given in the table below:
Topical antibiotic 1
Topical antibiotic 2
Topical antibiotic 3
3
5
8
9

17. 1
2
5
2
6
11
5
4
Conduct a one-way ANOVA to determine whether there is a
significance difference in the number of days to eliminate the
rash.