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BUA 6315: Business Analytics for Decision Making
Milestone 2: Regression Analysis Guidelines and Rubric
Overview:
The objective of this milestone is to fit and estimate a regression model to predict the response variable for the same dataset that you selected
in Milestone 1. You will document the key and relevant steps or plans, and include them in your report and appendices.
Prompt:
For detailed instructions on how to complete this milestone, please refer to the Milestone 2 handout for your specific dataset, available in
Blackboard:
1. College Admission Data
2. Tech Sales Rep Data
3. Longitudinal Survey Data
Submission Guidelines: Your final submission must be submitted as a 2- to 3-page Microsoft Word document with double spacing, 12-point
Times New Roman font, 1-inch margins, and should include the tables in an appendix.
Instructor Feedback: This activity uses an integrated rubric in Blackboard. Students can view instructor feedback in the Grade Center.
Rubric
1
Criteria Satisfactory (100%) Proficient (75%) Needs Improvement (55%) Not Evident (0%) Value
Estimate Model
Tables
Demonstrates a sophisticated
knowledge of regression
analysis by reporting results
of multivariate regression
analysis in a user-friendly
table that includes parameter
estimates and p-values of
each estimate (each model),
standard error of estimate
(Se), R-squared, adjusted
R-squared, and p-value of the
Results reported in a
user-friendly table that
includes parameter estimates
and p-values of each
estimate (each model),
standard error of estimate
(Se), R-squared, adjusted
R-squared, and p-value of the
F-test. The tables include a
footnote for significance
level(s) and additional
Reporting of results may be
incorrect or missing some of
the following: reported in a
user-friendly table that
includes parameter estimates
and p-values of each
estimate (each model),
standard error of estimate
(Se), R-squared, adjusted
R-squared, and p-value of the
F-test. The tables may not
Results not reported. 15
BUA 6315: Business Analytics for Decision Making
2
F-test. The tables include a
footnote for significance
level(s) and additional
information that a reader
needs to understand the
table.
information that a reader
needs to understand the
table.
include a footnote for
significance level(s) and
additional information that a
reader needs to understand
the table.
Best Multivariate
Regression Model
Demonstrates a
sophisticated knowledge of
regression analysis through
the explanation of why the
model chosen is the best
multivariate regression
model.
Explains why the model
chosen is the best
multivariate regression
model.
Identifies a model as the
best multivariate regression
model, but the explanation
why may be lacking in detail,
clarity, or accuracy.
Does not choose the best
multivariate regression
model.
7
Violations of Model
Assumptions
Demonstrates a
sophisticated knowledge of
regression analysis through
the determination of whether
any of the assumptions of
the linear regression model
are violated and if so,
describes ways to solve this
problem; or if there are no
violations, explains how that
was determined.
Determines whether any of
the assumptions of the linear
regression model are
violated and if so, describes
ways to solve this problem;
or if there are no violations,
explains how that was
determined.
Determines whether any of
the assumptions of the linear
regression model are
violated but may not
describe ways to solve this
problem; or if there are no
violations, may not explain
how that was determined.
Does not determine whether
any of the assumptions of
the linear regression model
are violated.
7
Multicollinearity Demonstrates a
sophisticated knowledge of
regression analysis through
the determination of whether
multicollinearity is an issue
and if not, explanation why.
Determines if
multicollinearity is an issue
and if not, explains why.
Determines if
multicollinearity is an issue
but if not, the explanation
why may be lacking in detail,
clarity, or accuracy.
Does not determine if
multicollinearity is an issue.
7
BUA 6315: Business Analytics for Decision Making
3
Significance of
Coefficients
Demonstrates a
sophisticated knowledge of
regression analysis through
the correct identification of
which predictor variables are
significant at the 5%
significance level; the
interpretation of R-squared
and coefficient estimates;
and explanation of each.
Explains which predictor
variables are significant at
the 5% significance level,
and interprets R-squared
and coefficient estimates.
Identifies predictor variables
as significant at the 5%
significance level, and
interprets R-squared and
coefficient estimates, but the
explanation why may be
unclear or the predictor
variables identified as
significant may be incorrect.
Does not explain which
predictor variables are
significant at the 5%
significance level, or interpret
R-squared and coefficient
estimates.
7
Comparison of
Results
Demonstrates a
sophisticated knowledge of
regression analysis through
the comparison of findings
and describes any
differences.
Compares findings and
describes any differences.
Compares findings but may
be lacking in detail, clarity, or
accuracy.
Does not compare findings. 7
Best Logistic
Regression Model
Demonstrates a
sophisticated knowledge of
regression analysis through
the explanation of why the
model chosen is the best
logistic regression model.
Explains why the model
chosen is the best logistic
regression model.
Identifies a model as the
best logistic regression
model, but the explanation
why may be lacking in detail,
clarity, or accuracy.
Does not choose the best
logistic regression model.
7
Accuracy Rate Demonstrates a
sophisticated knowledge of
regression analysis through
the determination of the
accuracy rate of the best
model.
Determines the accuracy
rate of the best model.
Accuracy rate of the best
model was unclear or
inaccurate.
Does not determine the
accuracy rate of the best
model.
5
BUA 6315: Business Analytics for Decision Making
4
Recommendations
and Suggestions
Demonstrates a
sophisticated knowledge of
regression analysis through
making recommendations
and suggestions based on
the regression analysis
findings to help the
organization make informed
decisions.
Makes recommendations
and suggestions based on
the regression analysis
findings to help the
organization make informed
decisions.
Recommendations and
suggestions are unclear or
inappropriate.
Does not make
recommendations or
suggestions.
20
Content of Report The content of the written
submission is well-presented
and argued; ideas are
detailed, developed and
supported with evidence,
data analysis, tables and
figures. A non-technical
audience can easily
understand the content.
The content of the written
submission is sound and
solid; ideas are present.
Most ideas are developed or
supported with evidence,
data analysis, tables, and
figures. It may include some
content that a non-technical
audience may find difficult to
understand.
The content of the written
submission is not sound.
Few ideas are presented,
and most of the ideas are not
developed or supported with
evidence, data analysis,
tables, and figures. The
report is too technical.
The content of the written
submission is inaccurate,
unsupported, or very
technical.
10
Mechanics No grammar or spelling
errors that distract the reader
from the content. Required
tables are clearly labeled.
Minor errors in grammar or
spelling that distract the
reader from the content.
Required tables may be
missing or not clearly
labeled.
Major errors in grammar or
spelling that distract the
reader from the content.
Tables are not included.
Critical errors related to
citations, grammar, spelling,
syntax, or organization that
prevent understanding of
ideas.
8
Total 100%
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