Running head: SPSS T-TEST
1
SPSS t Test Statistics Assignment
Deborah R. Davis
Liberty University
SPSS T-TEST
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The purpose of this document is to provide a response to the second SPSS assignment,
that for the use and understanding of the t test in statistics. The research scenario was given as a
part of the assignment, and presumes leaders of colleges and universities are seeking ways to
develop and maintain online and blended programs (Szapkiw, 2014, p. 2). This particular
assignment required the use of SPSS to “choose the appropriate t test . . . run the t test and
analyze the data” (Szapkiw, 2014, p. 9).
Structure
In that there are seven sections to this assignment and it is a small college paper, it will
only use the first two levels of headings, and it will be separated by assignment section.
Results part 1
In this section, the student is to determine the necessary assumption tests and their results,
including a conclusion about the tenability of the assumption and how it may influence the
results. To determine this the following question must be asked: Is there a difference between
the mean Perceived CAP Learning Scale (Rovai et al., 2009) scores for males and females who
are enrolled in the Introduction to Statistics course? Based on this question, the null hypothesis
we will be testing is: There is no statistical difference between the mean CAP scores of males
and females who are enrolled in the Introduction to Statistics course.
Assumptions are evaluated using the Levene’s test for equality of variances and
additional assumptions. The results of the Levene’s test , F (1,38) = 7.36, p = .01 indicate that
the variances of the two populations are not assumed to be approximately equal (the p < .05).
The means the assumption of equal variance is not tenable. Thus the equal variances not
assumed t test results were used.
Note that there are two assumption tests that needed to be completed for the t test. Don’t forget:
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1) Normality: This assumption assumes that the population distributions are normal. The t-test is
robust over moderate violations of this assumption, especially if a two-tailed test is used and the
sample size is not small (30+). Check for normality by creating a histogram or by conducting a
normality test, such as the Shapiro-Wilk and Kolmogorov-Smirnov tests. On the histogram,
normality is assumed when there is a symmetrical, bell shaped curve. For the normality tests,
non-significant results (a significance level more than .05) indicate tenability of the assumption.
That is, normality can be assumed. Using Analyze- Descriptive- Explore the following were
calculated:
Tests of Normality
Kolmogorov-Smirnova
Sex
Perceived_CAP_Learning
Statistic
df
Shapiro-Wilk
Sig.
Statistic
df
Sig.
Female
.250
20
.002
.835
20
.003
Male
.188
20
.063
.881
20
.019
_Scale
Results part 2
This particular assignment required elements to be presented from the data set provided.
An SPSS analysis of the mean, median, standard deviation variance, and range for the perceived
learning variable was performed.
Table 1.
Descriptive Statistics for the Perceived Learning Variable (N = 40)
n
M
Males
20
32.60
Females
20
42.25
Mdn
SD
V
Range
117.04
29.00
15.12
47.00
10.82
Results part 3
The null hypothesis we will be testing is: There is no statistical difference between the
mean CAP scores of males and females who are enrolled in the Introduction to Statistics course.
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Results part 4
The independent variable is Sex (Male and Female), and the dependent variable is the
CAP score. Since there is one categorical independent variable with two levels and one
continuous dependent variable and we want to know if there is a statistically significant
difference between the two groups, we will conduct an independent samples t-test.
Results part 5
An independent t test was conducted to evaluate whether a statistically signficant
difference exists between the mean Perceived CAP Learning Scale (Rovia et al., 2009) of males
and females who are enrolled in an introductory course that is both online and residential. The
results of the independent t test were significant, t (40) = 2.32, p = .03, d = 34.42, indicating that
there is a significant difference between the scores of males (M = 32.60, SD = 15.12, n = 20) and
the scores of females (M = 42.25, SD = 15.115, n = 20). Effect size was .124 indicating a large
magnitudee of difference in the means. The 95% confidence interval for the difference between
the means was 8.44 and 10.86.
Results part 6
The researcher did not fail to reject the null hypothesis. In that effect size was .124 as
computed by eta squared, null hypothesis: There is no statistical difference between the mean
CAP scores of males and females who are enrolled in the Introduction to Statistics course could
not be rejected.
Results part 7
The effect size was determined use the formula for eta squared (t squared / t squared +
(N1+N2-2). In this case, that means that 2.322 / 2.322 + (20+20-2) which equals .12. In that
effect ranges from zero to one, and .01 is considered a small effect with .06 a moderate effect
SPSS T-TEST
and .14 a large effect, therefore a score of .12 is quite large expressed in terms of percentage.
This shows that 12% of the variance is explained by sex.
5
SPSS T-TEST
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References
Rovai, A.P., Wighting M.J.. Baker, J.D., & Grooms, L.D. (2009). Development of an instrument
to measure perceived cognitive, affective, and psychomotor (CAP) learning in traditional
and virtual classroom higher education settings. Internet and Higher Education, 12(1), 713.
Szapkiw, A. (2014). Spss assignment instructions. In Lynchburg, VA: Liberty University.
Retrieved from http://amandaszapkiw.com/elearning/writing/downloads/ReportingStatisical-Results-in-APA-Format.pdf
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7
Appendix
SPSS Output
GET
FILE='C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_Set.sav'.
DATASET NAME DataSet1 WINDOW=FRONT.
T-TEST GROUPS=Sex(1 2)
/MISSING=ANALYSIS
/VARIABLES=Perceived_CAP_Learning_Scale
/CRITERIA=CI(.95).
T-Test
Notes
Output Created
31-JAN-2014 06:58:34
Comments
C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_
Data
Set.sav
Input
Active Dataset
DataSet1
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
Definition of Missing
Missing Value Handling
40
User defined missing values are treated as missing.
Statistics for each analysis are based on the cases with no missing or
Cases Used
out-of-range data for any variable in the analysis.
T-TEST GROUPS=Sex(1 2)
/MISSING=ANALYSIS
Syntax
/VARIABLES=Perceived_CAP_Learning_Scale
/CRITERIA=CI(.95).
Processor Time
00:00:00.03
Elapsed Time
00:00:00.37
Resources
[DataSet1] C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_Set.sav
SPSS T-TEST
8
Group Statistics
Sex
N
Mean
Std. Deviation
Std. Error Mean
Female
20
42.25
10.818
2.419
Male
20
32.60
15.115
3.380
Perceived_CAP_Learning_Scale
Independent Samples Test
Levene's Test for Equality of Variances
F
Equal variances assumed
Sig.
7.356
t
.010
df
2.322
Perceived_CAP_Learning_Scale
Equal variances not assumed
2.322
USE ALL.
COMPUTE filter_$=(Sex = 1).
VARIABLE LABELS filter_$ 'Sex = 1 (FILTER)'.
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'.
FORMATS filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE.
FREQUENCIES VARIABLES=Perceived_CAP_Learning_Scale
/NTILES=4
/NTILES=10
/PERCENTILES=95.0
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE SUM
/ORDER=ANALYSIS.
Frequencies
Notes
Output Created
31-JAN-2014 07:01:56
Comments
C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_Set.s
Data
av
Input
Active Dataset
DataSet1
Filter
Sex = 1 (FILTER)
Weight
<none>
Split File
<none>
N of Rows in Working Data File
Missing Value Handling
Definition of Missing
20
User-defined missing values are treated as missing.
34
SPSS T-TEST
Cases Used
9
Statistics are based on all cases with valid data.
FREQUENCIES VARIABLES=Perceived_CAP_Learning_Scale
/NTILES=4
/NTILES=10
Syntax
/PERCENTILES=95.0
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM
MEAN MEDIAN MODE SUM
/ORDER=ANALYSIS.
Processor Time
00:00:00.02
Elapsed Time
00:00:00.03
Resources
[DataSet1] C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_Set.sav
Statistics
Perceived_CAP_Learning_Scale
Valid
20
N
Missing
0
Mean
42.25
Median
47.00
25a
Mode
Std. Deviation
10.818
Variance
117.039
Range
29
Minimum
25
Maximum
54
Sum
845
10
25.20
20
27.40
25
29.75
30
32.90
40
45.00
50
47.00
60
48.00
70
50.00
75
50.75
80
52.60
Percentiles
SPSS T-TEST
90
53.90
95
54.00
10
a. Multiple modes exist. The smallest value is shown
Perceived_CAP_Learning_Scale
Frequency
Valid
Percent
Valid Percent
Cumulative Percent
25
2
10.0
10.0
10.0
27
2
10.0
10.0
20.0
29
1
5.0
5.0
25.0
32
1
5.0
5.0
30.0
35
1
5.0
5.0
35.0
45
2
10.0
10.0
45.0
47
2
10.0
10.0
55.0
48
2
10.0
10.0
65.0
50
2
10.0
10.0
75.0
51
1
5.0
5.0
80.0
53
2
10.0
10.0
90.0
54
2
10.0
10.0
100.0
20
100.0
100.0
Total
USE ALL.
COMPUTE filter_$=(Sex = 2).
VARIABLE LABELS filter_$ 'Sex = 2 (FILTER)'.
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'.
FORMATS filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE.
FREQUENCIES VARIABLES=Perceived_CAP_Learning_Scale
/NTILES=4
/NTILES=10
/PERCENTILES=95.0
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE SUM
/ORDER=ANALYSIS.
Frequencies
Notes
Output Created
31-JAN-2014 07:02:25
SPSS T-TEST
11
Comments
C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_Set.s
Data
av
Input
Active Dataset
DataSet1
Filter
Sex = 2 (FILTER)
Weight
<none>
Split File
<none>
N of Rows in Working Data File
20
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data.
Missing Value Handling
FREQUENCIES VARIABLES=Perceived_CAP_Learning_Scale
/NTILES=4
/NTILES=10
Syntax
/PERCENTILES=95.0
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM
MEAN MEDIAN MODE SUM
/ORDER=ANALYSIS.
Processor Time
00:00:00.02
Elapsed Time
00:00:00.04
Resources
[DataSet1] C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_Set.sav
Statistics
Perceived_CAP_Learning_Scale
Valid
20
N
Missing
0
Mean
32.60
Median
34.50
Mode
40
Std. Deviation
15.115
Variance
228.463
Range
42
Minimum
12
Maximum
54
Sum
652
10
14.10
20
16.00
Percentiles
SPSS T-TEST
25
16.50
30
18.30
40
24.00
50
34.50
60
40.00
70
45.00
75
46.50
80
49.40
90
51.90
95
53.90
Perceived_CAP_Learning_Scale
Frequency
Valid
Percent
Valid Percent
Cumulative Percent
12
1
5.0
5.0
5.0
14
1
5.0
5.0
10.0
15
1
5.0
5.0
15.0
16
2
10.0
10.0
25.0
18
1
5.0
5.0
30.0
19
1
5.0
5.0
35.0
22
1
5.0
5.0
40.0
27
1
5.0
5.0
45.0
29
1
5.0
5.0
50.0
40
3
15.0
15.0
65.0
45
2
10.0
10.0
75.0
47
1
5.0
5.0
80.0
50
1
5.0
5.0
85.0
51
1
5.0
5.0
90.0
52
1
5.0
5.0
95.0
54
1
5.0
5.0
100.0
20
100.0
100.0
Total
FILTER OFF.
USE ALL.
EXECUTE.
FREQUENCIES VARIABLES=Perceived_CAP_Learning_Scale
/NTILES=4
/NTILES=10
12
SPSS T-TEST
13
/PERCENTILES=95.0
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE SUM
/ORDER=ANALYSIS.
Frequencies
Notes
Output Created
31-JAN-2014 07:03:53
Comments
C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_Set.s
Data
av
Input
Active Dataset
DataSet1
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
40
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data.
Missing Value Handling
FREQUENCIES VARIABLES=Perceived_CAP_Learning_Scale
/NTILES=4
/NTILES=10
Syntax
/PERCENTILES=95.0
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM
MEAN MEDIAN MODE SUM
/ORDER=ANALYSIS.
Processor Time
00:00:00.03
Elapsed Time
00:00:00.04
Resources
[DataSet1] C:\Users\Ken\Documents\liberty\educ712\SPSS_Assignment_Data_Set.sav
Statistics
Perceived_CAP_Learning_Scale
Valid
40
N
Missing
Mean
0
37.43
SPSS T-TEST
Median
42.50
Mode
45
Std. Deviation
13.864
Variance
192.199
Range
42
Minimum
12
Maximum
54
Sum
1497
10
16.00
20
22.60
25
25.50
30
27.00
40
33.20
50
42.50
60
46.20
70
48.00
75
50.00
80
50.80
90
53.00
95
54.00
Percentiles
Perceived_CAP_Learning_Scale
Frequency
Percent
Valid Percent
Cumulative Percent
12
1
2.5
2.5
2.5
14
1
2.5
2.5
5.0
15
1
2.5
2.5
7.5
16
2
5.0
5.0
12.5
18
1
2.5
2.5
15.0
19
1
2.5
2.5
17.5
22
1
2.5
2.5
20.0
25
2
5.0
5.0
25.0
27
3
7.5
7.5
32.5
29
2
5.0
5.0
37.5
32
1
2.5
2.5
40.0
35
1
2.5
2.5
42.5
Valid
14
SPSS T-TEST
40
3
7.5
7.5
50.0
45
4
10.0
10.0
60.0
47
3
7.5
7.5
67.5
48
2
5.0
5.0
72.5
50
3
7.5
7.5
80.0
51
2
5.0
5.0
85.0
52
1
2.5
2.5
87.5
53
2
5.0
5.0
92.5
54
3
7.5
7.5
100.0
40
100.0
100.0
Total
15
You have a basic understanding of this analysis and are headed in the right direction. Please take
time to read my comments to learn where you can improve.
SPSS t Test Grading Rubric
Criteria
Description
Points
Earned
Points
Possible
Assumption
Testing
Identification
Candidate identified the appropriate assumption tests.
1.5
3
Assumption
Testing Results
Candidate reported the results for the appropriate assumption tests
and correctly reported the tenability of each test. Appropriate
graphs were included. If assumption was violated, the learner
noted it and discussed how the results could be influenced.
3.5
7
Descriptive
Statistics
Candidate reported the appropriate descriptive statistics. Tables
were provided where appropriate. Descriptives were correct.
10
10
Statistical
Procedure
Choice
Candidate chooses the correct statistical procedure based on the
proposed research question and case study. A rational for the
chosen statistical procedure is provided and logical; it is supported
by analysis resources
4
5
Statistical
Procedure
Candidate correctly reports the results of the primary analysis in
statistical form. Effect size, power, and confidence intervals were
reported where applicable.
8
10
Statistical
Procedure
Interpretation
Candidate correctly reports the results of the primary analysis in
narrative form. Interpretation of the results is included. Effect
size, power, and confidence intervals are interpreted were
included.
9
10
Null
Hypothesis
Candidate provides a null hypothesis that aligns with the research
question and appropriate statistical procedure.
5
5
SPSS T-TEST
16
Null
Hypothesis
Decision
Candidate correctly rejects or fails to reject the null hypothesis
based on the statistical results.
0
5
Grammar and
APA
Candidate uses correct APA, spelling, grammar, and punctuation.
Results are reported in accordance with the APA Manual. And, all
justifications and conventions used for interpretation are cited.
9
10
SPSS Output
Candidate includes SPSS output at the end of the submitted
document. SPSS output should not be included in the results
section; the output is only used to write a narrative and create
tables and figures in accordance with APA guidelines.
5
5
55
70
Total