Project Part C: Regression and Correlation Analysis

Project Part C: Regression and Correlation
Analysis
Your Instructor will
specify for you the dependent variable and the independent variables in your
Case and data. Using MINITAB perform the regression and correlation
analysis for the data by answering the following.
1.
Generate a scatterplot for the specified dependent variable and
the specified independent variable, including the graph of the “best
fit” line. Interpret.
2.
Determine the equation of the “best fit” line, which
describes the relationship between the dependent variable and the selected
independent variable.
3.
Determine the coefficient of correlation. Interpret.
4.
Determine the coefficient of determination. Interpret.
5.
Test the utility of this regression model (use a two tail test
with the ? provided by your Instructor). Interpret your results, including the
p-value.
6.
Based on your findings in 1-5, what is your opinion about using
the designated independent variable to predict the designated dependent
variable? Explain.
7.
Compute the confidence interval for beta-1 (the population slope),
using the confidence level specified by your Instructor. Interpret this
interval.
8.
Using an interval, estimate the average for the dependent variable
for a selected value of the independent variable (to be provided by your
Instructor). Interpret this interval.
9.
Using an interval, predict the particular value of the dependent
variable for a selected value of the independent variable (to be provided by
your Instructor). Interpret this interval.
10.
What can we say about the value of the dependent variable for
values of the independent variable that are outside the range of the sample values?
Explain your answer.
In an attempt to improve
the model, we will attempt to do a multiple regression model predicting the
dependent variable based on all of the independent variables.
11.
Using MINITAB run the multiple regression analysis using the designated
dependent and independent variables. State the equation for this multiple
regression model.
12.
Perform the Global Test for Utility (F-Test). Explain your
conclusion.
13.
Perform the t-test on each independent variable. Explain your
conclusions and clearly state how you should proceed. In particular, which
independent variables should we keep and which should be discarded. If any
independent variables are to be discarded, re-run the multiple regression,
including only the significant independent variables, and include the final
Minitab output, with interpretation.
14.
Is this multiple regression model better than the linear model
that we generated in parts 1-10? Explain.
15.
All DeVry University policies are in effect, including the
plagiarism policy.
16.
Project Part C report is due by the end of Week 7.
17.
Project Part C is worth 100 total points. See grading rubric
below.
Summarize your results from 1-14 in a report that is three pages
or less in length and explains and interprets the results in ways that are
understandable to someone who does not know statistics.
Submission: The summary report + all of the work done in 1-14
(Minitab Output + interpretations) as an appendix.
Format for report:
A.
Summary Report
B.
Points 1-14 addressed with appropriate output, graphs and interpretations.
Be sure to number each point 1-14.
Project Part C: Grading Rubric

Category

Points

%

Description

Questions
1 – 12 and 14 – 5 pts. each

65

65

addressed
with appropriate output, graphs and interpretations

Question
13

15

15

addressed
with appropriate output, graphs and interpretations

Summary

20

20

writing,
grammar, clarity, logic, and cohesiveness

Total

100

100

A
quality paper will meet or exceed all of the above requirements.

Location
Income ($1,000)
Size
Years
Credit Balance($)

Urban
27
1
2
2,631

Rural
25
4
2
2,047

Suburban
25
1
1
3,155

Suburban
26
1
2
3,913

Rural
30
5
5
2,660

Urban
29
1
3
3,531

Rural
33
6
10
2,766

Urban
30
1
4
3,769

Suburban
32
2
4
4,082

Urban
34
1
6
3,806

Urban
35
1
8
4,049

Urban
40
1
9
4,073

Rural
30
6
9
2,697

Rural
33
6
11
2,914

Urban
42
2
10
4,073

Suburban
32
2
4
4,310

Urban
43
2
10
4,199

Urban
43
2
10
4,253

Rural
33
7
13
3,104

Urban
47
2
10
4,293

Suburban
35
3
5
4,456

Urban
54
2
11
4,340

Suburban
42
3
5
4,925

Rural
36
7
13
3,178

Urban
57
3
11
4,391

Suburban
44
3
6
4,947

Rural
38
7
15
3,203

Urban
54
3
8
4,354

Urban
54
3
10
4,366

Suburban
46
4
6
5,003

Rural
40
7
15
3,250

Urban
60
4
11
4,402

Urban
58
4
10
4,397

Urban
61
5
13
4,595

Urban
61
5
13
4,786

Urban
62
6
14
4,888

Suburban
49
5
8
5,148

Urban
68
6
14
5,011

Suburban
57
6
8
5,220

Rural
45
8
16
3,257

Urban
71
7
15
5,528

Suburban
57
7
9
5,283

Suburban
64
8
9
5,332

Rural
45
8
17
3,304

Urban
74
7
19
5,553

Suburban
65
8
10
5,484

Rural
47
8
18
3,342

Rural
53
8
18
3,788

Suburban
66
8
10
5,756

Suburban
69
8
10
5,861