Educational Psychology 565 Practice Quiz (use α = .05 unless otherwise stated). 1. A small school district wants to know what type of teaching/learning is most effective at helping students learn to read. Three methods are proposed (top-down, bottom-up, and interactive). It is believed that the gender of the teacher may also be important in student learning, so the study also aims to determine if gender of the teacher is important. There are 12 schools in the district, and each school has 1 second grade class (each class has 10 students). Two female teachers and two male teachers’ classrooms are randomly assigned to each of the three methods (all 12 teachers have just been hired in the district). At the end of the year, the students all took a 100 item standardized multiple-choice reading test called the “EZreading” test (note: the analysis was performed at the student level). Coding: teachgender = gender of teacher: 1= men, 2 = women Teachmeth = teaching method (1=top-down, 2=bottom-up, 3=interactive) EZread = scores on the Ezread reading test Use SPSS output “SPSS printout for question 1”to help answer the parts below. a. What is/are the independent variable(s) in this experiment (Be specific)? What level of measurement is/are the IV(s)? Explain why? b. What is/are the dependent variable(s) in this experiment (Be specific)? What level of measurement is/are the DV(s)? Explain why? c. State the null hypotheses and alternative hypotheses for the factors and the interaction in symbols and words. d. Do you think the assumption of homogeneity of variance has been met? Support your answer. e. Do you think the assumption of independence has been met? Support your answer. f. Calculate Cohen’s d for the difference between the top-down and interactive methods. Explain what Cohen’s d means for this comparison. g. Is the interaction of the two factors statistically significant? Explain your answer. h. Report the results of the study along with an interpretation for the results. You do not need to write up the results like a results section; you can just report the findings with statements about each factor and the interaction of the two factors. Be sure to cite evidence from your analysis. i. Based on the results of the study what would you recommend about teaching method and gender of teachers? 2. Answer the following questions. Source SS df MS F Between 100 20 Within 2 50 Total 200 7 a. Complete the ANOVA source table (fill in all blank spaces) b. How many people are in this study. (hint: use degrees of freedom) c. What is the critical F at α = .01? Would you reject the null hypothesis? Explain your answer. d. What are the critical F at α = .05? Would you reject the null hypothesis? Explain your answer. e. Why do the conclusions from items c and d differ? Explain your answer in terms of Type I and II errors. 3. A researcher wants to kn.

1. Educational Psychology 565 Practice Quiz
(use α = .05 unless otherwise stated).
1. A small school district wants to know what type of
teaching/learning is most effective at helping students learn to
read. Three methods are proposed (top-down, bottom-up, and
interactive). It is believed that the gender of the teacher may
also be important in student learning, so the study also aims to
determine if gender of the teacher is important. There are 12
schools in the district, and each school has 1 second grade class
(each class has 10 students). Two female teachers and two male
teachers’ classrooms are randomly assigned to each of the three
methods (all 12 teachers have just been hired in the district). At
the end of the year, the students all took a 100 item
standardized multiple-choice reading test called the
“EZreading” test (note: the analysis was performed at the
student level).
Coding:
teachgender = gender of teacher: 1= men, 2 = women
Teachmeth = teaching method (1=top-down, 2=bottom-up,
3=interactive)
EZread = scores on the Ezread reading test
Use SPSS output “SPSS printout for question 1”to help answer
the parts below.
a. What is/are the independent variable(s) in this experiment
(Be specific)? What level of measurement is/are the IV(s)?
Explain why?

2. b. What is/are the dependent variable(s) in this experiment (Be
specific)? What level of measurement is/are the DV(s)? Explain
why?
c. State the null hypotheses and alternative hypotheses for the
factors and the interaction in symbols and words.
d. Do you think the assumption of homogeneity of variance has
been met? Support your answer.
e. Do you think the assumption of independence has been met?
Support your answer.
f. Calculate Cohen’s d for the difference between the top-down

3. and interactive methods. Explain what Cohen’s d means for this
comparison.
g. Is the interaction of the two factors statistically significant?
Explain your answer.
h. Report the results of the study along with an interpretation
for the results. You do not need to write up the results like a
results section; you can just report the findings with statements
about each factor and the interaction of the two factors. Be sure
to cite evidence from your analysis.
i. Based on the results of the study what would you recommend
about teaching method and gender of teachers?
2. Answer the following questions.

4. Source
SS
df
MS
F
Between
100
20
Within
2
50
Total
200
7
a. Complete the ANOVA source table (fill in all blank spaces)
b. How many people are in this study. (hint: use degrees of
freedom)
c. What is the critical F at α = .01? Would you reject the null

5. hypothesis? Explain your answer.
d. What are the critical F at α = .05? Would you reject the null
hypothesis? Explain your answer.
e. Why do the conclusions from items c and d differ? Explain
your answer in terms of Type I and II errors.
3. A researcher wants to know whether there are differences
between two teaching techniques and baseline in improving

6. math skills. Due to economic considerations he could not use a
between-subjects design. Therefore, he measured participants’
math skills at baseline, gave them teaching method A for two
weeks and measured their math skills, and then gave them
teaching method B for two weeks and measured their math
skills. On the measure low scores indicated low math skills.
Using the provided SPPS output to answer the following
questions:
a. Was the assumption of sphericity met? Explain your answer.
b. According to the omnibus test was there a difference between
baseline and/or the methods. Explain your answer.
c. Using the output from the pairwise comparisons. Explain
which levels of the within-subjects factor differ.
d. What is the primary weakness of this design?
SPSS printout for question 1.

7. 1. Teachmeth
2. Teachgender
3. Teachmeth * Teachgender
SPSS printout for question 3.

8. 5
Estimates
Dependent Variable: Ezread
74.025
1.612
70.831
77.219
70.225
1.612
67.031
73.419
64.750
1.612
61.556
67.944
Teachmeth
1
2
3
Mean
Std. Error
Lower Bound
Upper Bound
95% Confidence Interval
Pairwise Comparisons
Dependent Variable: Ezread
3.800
2.280
.098
-.717
8.317

9. 9.275
*
2.280
.000
4.758
13.792
-3.800
2.280
.098
-8.317
.717
5.475
*
2.280
.018
.958
9.992
-9.275
*
2.280
.000
-13.792
-4.758
-5.475
*
2.280
.018
-9.992
-.958
(J) Teachmeth
2
3
1
3
1
2

10. (I) Teachmeth
1
2
3
Mean
Difference
(I-J)
Std. Error
Sig.
a
Lower Bound
Upper Bound
95% Confidence Interval for
Difference
a
Based on estimated marginal means
The mean difference is significant at the .05 level.
*.
Adjustment for multiple comparisons: Least Significant
Difference (equivalent to no adjustments).
a.
Estimates
Dependent Variable: Ezread
70.083
1.316
67.475
72.691
69.250
1.316
66.642
71.858
Teachgender
1
2
Mean
Std. Error

11. Lower Bound
Upper Bound
95% Confidence Interval
Pairwise Comparisons
Dependent Variable: Ezread
.833
1.862
.655
-2.855
4.522
-.833
1.862
.655
-4.522
2.855
(J) Teachgender
2
1
(I) Teachgender
1
2
Mean
Difference
(I-J)
Std. Error
Sig.
a
Lower Bound
Upper Bound
95% Confidence Interval for
Difference
a
Based on estimated marginal means
Adjustment for multiple comparisons: Least Significant
Difference (equivalent to no adjustments).
a.

12. Estimates
Dependent Variable: Ezread
74.150
2.280
69.633
78.667
73.900
2.280
69.383
78.417
70.600
2.280
66.083
75.117
69.850
2.280
65.333
74.367
65.500
2.280
60.983
70.017
64.000
2.280
59.483
68.517
Teachgender
1
2
1
2
1
2
Teachmeth
1
2

13. 3
Mean
Std. Error
Lower Bound
Upper Bound
95% Confidence Interval
Pairwise Comparisons
Dependent Variable: Ezread
.250
3.225
.938
-6.138
6.638
-.250
3.225
.938
-6.638
6.138
.750
3.225
.817
-5.638
7.138
-.750
3.225
.817
-7.138
5.638
1.500
3.225
.643
-4.888
7.888
-1.500
3.225
.643

14. -7.888
4.888
(J) Teachgender
2
1
2
1
2
1
(I) Teachgender
1
2
1
2
1
2
Teachmeth
1
2
3
Mean
Difference
(I-J)
Std. Error
Sig.
a
Lower Bound
Upper Bound
95% Confidence Interval for
Difference
a
Based on estimated marginal means
Adjustment for multiple comparisons: Least Significant
Difference (equivalent to no adjustments).
a.
Teachgender

15. FemaleMale
Estimated Marginal Means
75
72.5
70
67.5
65
3
2
1
Teachmeth
Estimated Marginal Means of Ezread
Mauchly's Test of Sphericity
b
Measure: MEASURE_1
.980
.062
2
.970
.980
1.000
.500
Within Subjects Effect
factor1
Mauchly's W
Approx.
Chi-Square
df
Sig.
Greenhous
e-Geisser
Huynh-Feldt
Lower-bound
Epsilon
a
Tests the null hypothesis that the error covariance matrix of the

16. orthonormalized transformed dependent variables is
proportional to an identity matrix.
May be used to adjust the degrees of freedom for the averaged
tests of significance. Corrected tests are displayed in
the Tests of Within-Subjects Effects table.
a.
Design: Intercept
Within Subjects Design: factor1
b.
Tests of Within-Subjects Effects
Measure: MEASURE_1
11.200
2
5.600
5.508
.031
11.200
1.960
5.714
5.508
.032
11.200
2.000
5.600
5.508
.031
11.200
1.000
11.200
5.508
.079
8.133
8
1.017
8.133
7.840

17. 1.037
8.133
8.000
1.017
8.133
4.000
2.033
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Source
factor1
Error(factor1)
Type III Sum
of Squares
df
Mean Square
F
Sig.
Estimates
Measure: MEASURE_1
4.400
.600
2.734
6.066
4.000
.548
2.479
5.521
6.000
.316

18. 5.122
6.878
factor1
Baseline
Method A
Method B
Mean
Std. Error
Lower Bound
Upper Bound
95% Confidence Interval
Pairwise Comparisons
Measure: MEASURE_1
.400
.600
.541
-1.266
2.066
-1.600
.678
.078
-3.483
.283
-.400
.600
.541
-2.066
1.266
-2.000
*
.632
.034
-3.756
-.244
1.600
.678

19. .078
-.283
3.483
2.000
*
.632
.034
.244
3.756
(J) factor1
2
3
1
3
1
2
(I) factor1
1
2
3
Mean
Difference
(I-J)
Std. Error
Sig.
a
Lower Bound
Upper Bound
95% Confidence Interval for
Difference
a
Based on estimated marginal means
The mean difference is significant at the .05 level.
*.
Adjustment for multiple comparisons: Least Significant
Difference (equivalent to no

20. adjustments).
a.
Between-Subjects Factors
40
40
40
60
60
1
2
3
Teachmeth
1
2
Teachgender
N
Tests of Between-Subjects Effects
Dependent Variable: Ezread
1767.967
a
5
353.593
3.400
.007
582413.333
1
582413.333
5600.742
.000
1739.217
2
869.608
8.363
.000
20.833
1

21. 20.833
.200
.655
7.917
2
3.958
.038
.963
11854.700
114
103.989
596036.000
120
13622.667
119
Source
Corrected Model
Intercept
Teachmeth
Teachgender
Teachmeth *
Teachgender
Error
Total
Corrected Total
Type III Sum
of Squares
df
Mean Square
F
Sig.
R Squared = .130 (Adjusted R Squared = .092)
a.
Levene's Test of Equality of Error Variances
a
Dependent Variable: Ezread

22. .010
5
114
1.000
F
df1
df2
Sig.
Tests the null hypothesis that the error variance of
the dependent variable is equal across groups.
Design:
Intercept+Teachmeth+Teachgender+
Teachmeth * Teachgender
a.
MAT 312
Test 2 Chapters 8, 9 & 12 (180 Total Points)
Show All Work!
Name:_______________
1. Construct a 95% confidence interval for the mean of a normal
population if a random sample of size 60 from the population
yields a sample mean of 90 and the population has a standard
deviation of 10. What is the confidence interval and margin of
error (10 points)?
2. Forty panels were exposed to various corrosive conditions to
measure the protective ability of paint. The mean life for the
samples was 112 hours. The life of the paint samples is assumed
to be normally distributed with a population standard deviation
of 25 hours. Find the 85% confidence interval and margin of
error for the mean life of the paint (10 points).
3. Construct a 98% confidence interval for the mean of a normal
population assuming that the values listed below comprise a

23. random sample taken from the population. The population
standard deviation is unknown. Also, what are the mean and
sample standard deviation (15 points).
22
30
15
9
2
4
27
16
29
4. Suppose you sample 19 baseball pitchers and find that they
have an average pitching speed of 87 mph with a standard
deviation of 0.98 mph. Find a 95% confidence interval for the
average pitching speed of all pitchers (10 points).
5. A tire manufacturer is testing the tire pressure in its new
tires. A random sample of 10 tire pressure readings, yield a
variance of 31.8. Construct and interpret a 95% confidence
interval for the variance (10 points).
6. Find the t – value such that .025 area of the area under the
curve is to the left of the t – value. Assume the degree of
freedom is 100 (5 points).
7. Find tα/2,n-1 for area two tails the following combinations
of α and n (5 points each):
a. α=.05, n=25
b. α=.20, n=3
8. Find zα/2 for the following confidence levels (5 points each):

24. a. 80%
b. 70%
9. Find zα/2 for the following levels of α (5 points each):
a. α=.66
b. α=.30
10. A state politician is interested in knowing how voters in
rural areas and cities differ in their opinions about gun control.
For his study, 80 rural voters were surveyed, and 47 were found
to support gun control. Also, 80 voters from the cities were
surveyed, and 59 of these voters were found to support gun
control. Construct and interpret a 90% confidence interval and
margin of error for the true difference between the proportion of
rural and city voters who favor gun control (10 points).
11. John believes that his wife’s cell phone battery does not last
as long as his cell phone battery. On eight different occasions,
he measured the length of time his cell phone battery lasted, and
calculated that the mean was 26.9 hours with a standard
deviation of 6.5 hours. He measured the length of time his
wife’s cell phone battery lasted on nine different occasions and
calculated a mean of 24.1 with a standard deviation of 8.9.
Construct and interpret a 95% confidence interval for the true
difference in battery life between John’s cell phone and his
wife’s cell phone. (10 points each)
a. Assume the population variances are the same
b. Assume the population variances are different
12. Students from two different schools took the same
standardized test.
From school A, a random sample of 53 students had a mean
score of 80. From school B, a random sample of 44 students had

25. mean score of 84. Assume the population standard deviations
are 9 for school A and 5 for school B. Construct and interpret a
90% confidence interval for the true difference between the
mean test scores of the two schools. Also, what is the point
estimate? (15 points)
13. A dietician wants to see how much weight a certain diet can
help her 9 patients lose. She weighs each patient before and 45
days later. Her results are in the table. Construct and interpret a
98% confidence interval and calculate the paired differences for
the true mean difference between the weights to determine the
mean amount of weight lost by going on this diet (15 points).
Patients’ Weights (in Pounds)
Starting Weights
164
189
205
155
139
224
268
186
151
Ending Weights
157
178
191
152
137
207
249
173
146
d

26. 14. A teacher wants to have his students in two different classes
evaluate his teaching on a scale of 1-10 with 10 being excellent.
The results of the first class with 18 students was a mean of 5.8
with a standard deviation of 1.2, and the second class with 15
students was a mean of 7.2 with a standard deviation of 1.5.
Construct and interpret a 95% confidence interval to estimate a
true difference between the two classes. Assume that the
population variances are different (10 points).
15. For the data below, complete the following (20 points):
Age
34
43
49
51
65
Bone Density
946

27. 875
804
723
691
a. Draw a scatter plot
b. Estimate the correlation in words (positive, negative, or
none)
c. Explain your estimation
d. Calculate the correlation coefficient (r-value)
e. Explain what the correlation coefficient (r) tells about the
data
f. Calculate the coefficient of determination (r2)
g. Explain what the coefficient of determination tells about the
data
h. Calculate the least-squares regression line (line of best fit)
i. Predict the bone density at age 56