Essay Grade

To prepare for this Assignment:
•
Consider how a correlation analysis will ef f ectively allow you to answer relevant research
questions.
•
Review the video, Correlation and Introduction to Regression.
•
Review the f ollowing tutorials f rom the Green and Salkind text:
•
o
Lesson 16A, “Creating an SPSS Graph”
o
Lesson 16B, “Creating an SPSS Chart”
o
Lesson 31, “Pearson Product-Moment Correlation Coef f icient”
o
Lesson 32, “Partial Correlations”
o
Lesson 33, “Bivariate Linear Regression”
o
Lesson 34, “Multiple Linear Regression”
o
Lesson 35, “Discriminant Analysis”
Review the Assignment Exemplar document provided.
Submit a 5- to 6-page paper using the Assignment Exemplar.
Your paper must include the f ollowing elements:
•
An APA Results section f or the Pearson’s correlation test which includes all scale
variables. (See an example of an APA Results Section in Lesson 31 of the Green and
Salkind text.)
•
The critical elements of your SPSS output, including:
o
A properly f ormatted research question
o
A properly f ormatted H10 (null) and H1a (alternate) hypothesis
o
A descriptive statistics narrative and properly f ormatted descriptive statistics table
(see page 189 of the Green and Salkind text)
o
A properly f ormatted scatterplot graph (see pages 65-66 and page 191 of the Green
and Salkind text)
o
A properly f ormatted inf erential APA Results Section (see pages 191-192 of the
Green and Salkind text)
o
•
An appendix including the SPSS output generated f or descriptive and inf erential
statistics (see SPSS output on page 189 of the Green and Salkind text)
Finally, explain the dif f erences and similarities of Bivariate correlation analysis and
Bivariate regression analysis.
The page should have the following criteria’s.
Complete
Student submits a 5- to 6-page paper presenting the
results of running a correlation analysis.
Research
Question
Student submits a properly formatted research question.
Hypothesis
Student submits a properly formatted null and alternate
hypothesis.
Descriptive
Statistics
Student submits a descriptive statistics narrative and
properly formatted descriptive statistics table.
Scatterplot
Student submits a properly formatted scatterplot graph.
Results Section
Student submits a properly formatted inferential APA
Results Section.
Appendix
Student submits an appendix including the SPSS output
generated for descriptive inferential statistics.
Bivariate
Student explains the differences and similarities of
Correlation and Bivariate correlation analysis and Bivariate regression
Regression
analysis.
Week Six Correlation Exemplar Template
Research Question
Do men who have a positive self-concept in one life domain tend to have a
positive self-concept in other domains, and conversely, do men who have a negative selfconcept in one domain tend to have a negative self-concept in other domains?
Hypotheses
H0: Men who have a positive self-concept in one life domain do not tend to have a
positive self-concept in other domains, and conversely, men who have a negative selfconcept in one domain do not tend to have a negative self-concept in other domains.
H1: Men who have a positive self-concept in one life domain tend to have a
positive self-concept in other domains, and conversely, men who have a negative selfconcept in one domain tend to have a negative self-concept in other domains.
Results
Correlation coefficients were computed among five self-concept scales. Using the
Bonferroni approach to conrol for Type 1 error across 10 correlations, a p value of less
than .005 (.05/10) was required for significance. Table 1 depicts the descriptive statistics
of the study variables. The results of the correlation analyses presented in Table 2 show
that 7 out of the 10 correlations were statistically significant and were greater than or
equal to .35. The correlation of scholarly knowledge self-concept with the other selfconcept measures tended to be lower and not significant. In general, the results suggest
that if men say that they have a positive self-concept in one domain, they tend to state
that they have a positive self-concept in other domains, except for scholarly knowledge.
The appendix depicts the SPSS correlation output generated by the analysis. Figure 1
depicts a scatterplot matrix of the variables.
Table 1
Descriptive Statistics for the Study Variables (N = 80)
Variable
M
SD
Intimate Relationships
50.48
6.18
Friends
53.98
6.91
Common Sense
52.23
7.32
Academic Intelligence
47.94
9.17
General
53.79
4.90
Table 2
Correlations Among the Five Self-Concept Scales (N = 80)
Self-Concept Scales
Intimate
Relationships
.55
Common
Sense
.35
Academic
Intelligence
.22
Friends
General
.39
–
Friends
.55
–
.46
.24
.55
Common Sense
.35
.46
–
.40
.53
Academic Intelligence
.22
.24
.40
–
.26
General
.39
.55
.53
.26
–
Intimate Relationships
Figure 1. Scatterplot matrix
Appendix
Descriptive Statistics
Mean
Intimate Relationships
Friends
Common Sense
Academic Intelligence
General
50.48
53.98
52.23
47.94
53.79
Std. Deviation
6.183
6.910
7.323
9.168
4.890
N
80
80
80
80
80
Correlations
Intimate
Relationships
Pearson Correlation
Intimate Relationships
Friends
Common Sense
Academic Intelligence
General
1
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
Friends
Common
Sense
Academic
Intelligence
General
.552**
.351**
.218
.393**
.000
.001
.052
.000
80
1
80
.462**
.000
80
1
80
.244*
.029
80
.400**
.000
80
1
80
.546**
.000
80
.525**
.000
80
.261*
.019
80
1
80
.552**
.000
80
.351**
.001
80
.218
.052
80
.393**
80
.462**
.000
80
.244*
.029
80
.546**
.000
.000
.000
.019
80
80
80
80
80
.400**
.000
80
.525**
80
.261*
80

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