GC BUS660 Full Course – Discussions and Assignments- July 2016

GC BUS 660 week 1 DQ 1 & DQ 2

dq 1

Present an example of a business situation that you believe
would lend itself to the use of a quantitative business model. Clearly explain
how the model could be used in this situation.

dq 2

Multiple models are often used in supporting business
decision making. Outline a situation in your organization or industry that
required the need for multiple models. What factors were unique to this
situation? Support your response with rationale from the readings or external
research.

 

GC BUS 660 week 2 DQ 1 & DQ 2

dq 1

Apply a business decision model to something you do every
day, such as select an outfit, order lunch, or determine your exercise routine.
Be creative in your approach. How did you select the model? Include rationale
with support from the readings.

dq 2

Using the decision tree resources available in the Topic
Materials, create a decision tree for the scenario you outlined in Topic 2 DQ
1. Attach the decision tree to your response and include insights in crafting
the decision tree. How would you apply your experience to larger-scale
decisions at an organizational level?

 

GC BUS 660 week 3 DQ 1 & DQ 2

dq 1

Identify two business situations or problems within your
current organization or industry. Articulate how one of these lends itself to a
simple linear regression and how one does not. Why is simple linear regression
appropriate to address one situation or problem but not the other? Support your
ideas with evidence from the readings.

dq 2

You are the vice president of sales for TerraFirma, a
company that manufactures outdoor sporting gear. You receive a report on your
desk one morning that claims little or no relationship between the University
of Michigan Consumer Sentiment Index (CSI) and outdoor sporting gear sales. The
claim is based on a very low R2 of the simple regression model, using these two
variables (CSI and sales). Discuss how you would (or should) react to this
report and why. What clarifying questions might you ask?

 

GC BUS 660 week 4 DQ 1 & DQ 2

dq 1

Provide an example based on your professional experience of
a situation in which using a multiple regression model or nonlinear regression
model may have helped your organization make a better decision.

dq 2

What types of business situations or problems might best
lend themselves to multiple linear regression? What types may not? When do you
anticipate using a multiple linear regression model in your postgraduate,
professional experience? Explain.

 

GC BUS 660 week 5 DQ 1 & DQ 2

dq 1

Discuss the strategic importance of forecasting at your
organization (or one with which you are familiar). What strategic decisions
does it need to make in terms of forecasting? Provide two recent examples. In
your opinion, was this the best way? How could the process be improved?

dq 2

Refer to the Topic Material, “Chapter 1 – Fundamental
Issues in Business Forecasting.” This resource includes a discussion of
unrealistic expectations and forecast accuracy. How have you seen this
demonstrated in your organization or industry? Describe the forecasting
scenario and the “prediction” that did not come true. What
conversations did management have surrounding this issue? How would you
mitigate expectations for a situation like this in the future?

 

GC BUS 660 week 6 DQ 1 & DQ 2

dq 1

Identify two key strategic decisions made by your current
team, department, or organization. How could those decisions have been enhanced
by optimization models? Support your rationale with evidence from readings or
external research.

dq 2

Find a current example of a linear optimization model used
in your industry. Describe the industry’s needs, including any unique factors,
how the linear optimization model was used, and the problem or challenge it
addressed. Would you suggest a different model be used? Why or why not? Support
your response with rationale from the assigned readings.

 

GC BUS 660 week 7 DQ 1 & DQ 2

dq 1

Explain the importance of correctly stating the objective
function and constraints in linear optimization problems. Using examples from
your professional experience, describe the problems that could result if the
objective function and constraints are not stated properly. Why did these
problems arise? Support your anecdotal evidence with support and rationale from
the readings.

dq 2

Describe a workforce scheduling, a blending, and a logistics
problem facing your current organization or industry. What is being optimized
in each of your examples and why? How do linear optimization techniques differ
from decision tree analysis? Which are more applicable to the examples you
identified? Support your response with rationale from the readings.

 

GC BUS 660 week 8 DQ 1 & DQ 2

dq 1

Describe a current problem facing your department, organization,
or industry that would indicate the need for simulation. What key factors of
this business situation indicate the need for simulation (versus the other
modeling techniques covered in the course)? Support your response with
rationale from the readings.

dq 2

Consider some of the examples you have brought up in earlier
topics. Describe the key differences between simulation models and the models
covered earlier in the course. Outline how the approach to solving this problem
would differ in terms of applying and computing/solving the models.

 

 

 

GC BUS 660 week 1 Ethical Decision-Making Essay Assignment

Details:

Throughout this course, you will participate in a variety of
critical thinking exercises designed to engage you in evaluating and selecting
appropriate quantitative models and methods. A key aspect of this process
involves ethical considerations. In an essay of 750-1,000 words, explore
ethical decision making and arrive at conclusions relevant to your industry and
perspectives of Christian worldview.

How do ethical business practices influence the evaluation,
selection, and application of an analytical, quantitative business model? How
does the selection of an appropriate business model reflect ethical practice?
Frame your ethical considerations from both a Christian worldview and business
practice perspective.

What role do individuals and management play in ensuring the
appropriate business model is chosen, used, and evaluated for effectiveness?

Support your assertions with evidence from the readings,
external research, and the textbook.

Prepare the assignment according to the guidelines found in
the APA Style Guide, located in the Student Success Center. An abstract is not
required.

This assignment uses a rubric. Please review the rubric
prior to beginning the assignment to become familiar with the expectations for
successful completion.

You are required to submit this assignment to Turnitin.
Please refer to the directions in the Student Success Center.

 

 

 

GC BUS 660 week 2 Decision Analysis Case Study: Valley of
the Sun Reviews Assignment

Details:

For many of the remaining topics in BUS-660, assignments
will be in the form of case studies. These case studies are designed to provide
an opportunity to engage in that topic’s quantitative analysis method, as well
as demonstrate critical thinking and appropriate professional communication.

Review “Decision Analysis Case Study: Valley of the Sun
Reviews” for this topic’s case study, a proposal to change the faculty
performance review process at Valley of the Sun Academy (VSA).

Based on the information presented in the case study, create
a decision tree or Excel-based analysis to determine the most appropriate
recommendation.

In a 500-750-word report to VSA’s Human Resources department
and the chief financial officer, explain your approach and the rationale for
this method. Evaluate both outcomes and how they would be applied to this
decision. Conclude your report with your recommendation for the review process
VSA should adopt.

Submit your Excel-based analysis or decision tree with your
report.

Prepare the assignment according to the guidelines found in
the APA Style Guide, located in the Student Success Center. An abstract is not
required.

This assignment uses a rubric. Please review the rubric
prior to beginning the assignment to become familiar with the expectations for
successful completion.

You are required to submit this assignment to Turnitin.
Please refer to the directions in the Student Success Center.

Decision Analysis Case Study:

Valley of the Sun Reviews

Valley of the Sun Academy (VSA) is an online school
specializing in GED programs for the Phoenix area. Valley of the Sun Academy
enrolls 813 students and has a part-time faculty pool of 65 online instructors.

Online faculty are reviewed annually and provided with
feedback about their facilitation techniques, content expertise, engagement,
and classroom management. If necessary, remediation and additional support are
provided by the Faculty Advisory Board (FAB). The online faculty reviews are
one factor used to determine overall performance, teaching status, and
potential performance appraisals.

Recently, the FAB submitted a proposal for a new approach
for the next fiscal year, the Peer Faculty Performance Review (PFPR). Human
Resources (HR) and the school’s chief financial officer are evaluating the
suggestion against the current design, described by VSA’s director. Both review
processes are outlined below.

Current Design

Valley of the Sun Academy uses an external firm, TeachBest
Consulting, to conduct annual reviews for online faculty. The review team is
composed of faculty members at other online institutions, including
universities and high schools. Valley of the Sun Academy faculty are not part
of the review process, and TeachBest Consulting handles hiring and training
internally. Valley of the Sun Academy’s HR department assigns completed courses
to review, and VSA’s Technical Support team is responsible for providing
access.

Once completed, the TeachBest consultant submits the review
form toVSA’s HR department, and HR submits a payment for each review. In
addition, VSA has an annual contract with TeachBest Consulting.

The overall contract is $2,500/year. If VSA’s enrollment
reaches 1,000 or more students or their faculty pool expands to 75 or more
instructors, the contract amount will increase to $5,000/year. There is a 75%
chance the student enrollment will reach 1,000 students within the next
18months and a 25% chance enrollment will not increase. During the next nine
months,Human Resourcesanticipates hiring at least six math instructors.

Individual reviewers are paid $75 for each review. Reviews
are conducted in March, July, and November, with all faculty reviewed by
December 1.

Valley of the Sun Academy is responsible for disseminating
the results of the review to faculty members. If questions arise about review
results, the FAB is responsible for verifying the review and responding to the
instructor. Periodically, the Faculty Advisory Board finds fault with the
initial review and follow-up must be scheduled. Each year, about 5% of the
initial reviews are found to be inaccurate and new reviews must be scheduled.
Valley of the Sun Academy pays a discounted price of $50 for each follow-up
review.

Peer Faculty Performance Review (PFPR) Proposal

The FAB proposes to conduct faculty reviews in-house and no
longer contract TeachBest Consulting. Human Resourceswill review faculty files
and invite the top three performing instructors in four disciplines (Literacy
and Communication, Social Sciences, Math, and Science and Technology) to join
the PFPR committee.

Initial responsibilities will involve creating a new review
form and conducting a norming session for consistency. There will be ongoing
technology fees of $20/month for each reviewer, to ensure access to create and
complete the review forms. There will also be an initial cost to set up the
norming session. The Faculty Advisory Board recommends one of three options:

1. A $500 session that can be scheduled at any time with
TeachBest Consulting.

2. A $750 session offered monthly by an external employee
development firm.

3. A session designed by VSA’s HR and instructional design
specialists, which would be free to attend but would require internal time and
labor costs; HR anticipates a start of two months from implementation would
prevent interrupting normal business practices.

Because the responsibilities are not included in current
faculty contracts, FAB recommends stipends of $50 for each review completed.
With the new internal PFPR process, FAB anticipates faculty reviews would no
longer be overturned and there would not be a need to conduct secondary
reviews. Additionally, FAB expects reviews to move to a 9-month rolling cycle
rather than once every academic year.

 

 

GC BUS 660 week 3 Simple Regression Models Case Study:
Mystery Shoppers Assignment

Details:

Review “Simple Regression Models Case Study: Mystery
Shoppers” for this topic’s case study, a request to evaluate consignment
stores from mystery shopper data.

Based on the information presented in the case study, create
a regression model to determine the most appropriate recommendation.

Prepare a 250-500-word response to Mrs. Turner’s questions
about predicting final scores, statistical significance, and whether a store
location should be closed based on the data provided. Explain your approach and
the rationale for this method. Evaluate the outcomes of your regression model
and the responses to Mrs. Turner’s questions.

Submit a copy of the Excel spreadsheet file you used to
design your regression model and to determine statistical significance.

Note: Students should use Excel’s regression option to
perform the regression.

Use an Excel spreadsheet file for the calculations and
explanations. Cells should contain the formulas (i.e., if a formula was used to
calculate the entry in that cell).

Mac users can use StatPlus:mac LE, free of charge, from
AnalystSoft.

StatPlus:mac LE can be used with Excel 2011 to perform
statistical functions.

Go to the AnalystSoft Web site and follow the installation
instructions:http://www.analystsoft.com/en/products/statplusmacle/

Once installed, Apple users can use StatPlus:mac LE to
complete homework problems that require the use of Excel’s data analysis
statistical functions.

Prepare the written portion of this assignment according to
the guidelines found in the APA Style Guide, located in the Student Success
Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric
prior to beginning the assignment to become familiar with the expectations for
successful completion.

You are not required to submit this assignment to Turnitin.

Simple Regression Models Case Study: Mystery Shoppers

Chic Sales is a high-end consignment store with several
locations in the metro area. The company noticed a decrease in sales over the
last fiscal year. Research indicated customer satisfaction had decreased and
the owner, Pat Turner, decided to create a mystery shopper program.

The mystery shopper program lasted over a 6-month period,
employing several loyal and new customers assigned to each location. Surveys
were on a 100-point scale and involved categories such as “Staff Attitude,”
“Store Cleanliness,” “Product Availability,” and “Display(s) Appeal.”

After the mystery shopper period concludes, Mrs. Turner
sends you the following e-mail:

From:Pat Turner

Sent:Thursday, July 7, 2016 8:57 a.m.

Subject:Mystery Data Shopper Stats and Store
Performance?

Good morning! Welcome back from vacationJ I hope you had a
wonderful Fourth of July.

The last mystery shopper surveys came in and I have the
final numbers. I am interested in whether there is a way to predict the final
average based on the initial survey score.Also, is there a statisticallysignificant
relationship between how stores initially performed and what the overall
average is?

The initial survey score and the final average data for all
seven store locations is in the table below:

Store 1 2 3 4 5 6 7
Initial Survey Score 83 97 84 72 85 64 93
Final Average 78 98 92 75 88 70 93

Also, how good is the relationship between Initial Survey
Score and the Final Average? Could I use an Initial Survey Score to predict a
Final Average? In fact, could I predict a Final Average if I have an Initial
Survey Score of 90?

If you could have this to me before the weekend, that would
be great.

Thanks so much!

Pat Turner, Owner

Chic Sales Consignment, LLC

 

 

 

GC BUS 660 week 4 Multiple Regression Models Case Study:
Web Video on Demand Assignment

Details:

Review “Multiple Regression Models Case Study: Web
Video on Demand” for this topic’s case study, predicting advertising sales
for an Internet video-on-demand streaming service.

After developing Regression Model A and Regression Model B,
prepare a 250-500-word executive summary of your findings. Explain your
approach and evaluate the outcomes of your regression models.

Submit a copy of the Excel spreadsheet file you used to
design your regression model and to determine statistical significance.

Note: Students should use Excel’s regression option to
perform the regression.

Use an Excel spreadsheet file for the calculations and
explanations. Cells should contain the formulas (i.e., if a formula was used to
calculate the entry in that cell). Students are highly encouraged to use the
“Multiple Regression Dataset” Excel resource to complete this
assignment.

Mac users can use StatPlus:mac LE, free of charge, from
AnalystSoft.

Prepare the written portion of this assignment according to
the guidelines found in the APA Style Guide, located in the Student Success
Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric
prior to beginning the assignment to become familiar with the expectations for
successful completion.

You are required to submit this assignment to Turnitin.
Please refer to the directions in the Student Success Center.

Multiple Regression Models Case Study: Web Video on Demand

Web Video on Demand (WVOD) is an Internet video-on-demand
streaming service. The company offers a subscription service for $5.99/month,
which includes access to all programming and 30-second commercial intervals.

In the last year, the company has recently begun producing
its own programming, including 30-, 60-, and 120-minute television shows, specials,
and films. Programming has been developed for teen audiences as well as adults.

The following data represent the amount of money brought in
through advertising sales, the average number of viewers, length of the
program, and the average viewer age per program.

Advertising Sales

($)

Average # of Viewers

(Millions)

Length of Program (Minutes) Average Viewer Age

(Years)

28,000 10.1 30 30
25,500 11.4 30 25
31,000 19.9 60 30
29,000 13.6 60 38
20,500 12.5 60 20
14,500 3.5 30 15
27,000 15.1 60 24
23,500 3.7 30 17
19,500 4.3 30 19
23,000 12.2 120 45
18,000 5.1 120 19
29,500 15.9 60 28
30,000 16.8 120 31
25,000 8.5 120 58
22,500 9.1 30 43

The WVOD executives are in the process of evaluating a
partnership with several independent filmmakers to fund and distribute socially
conscious and diverse programming. The executives have asked for regression
models to be developed based on specific needs. The three regression model
requests and programming details are included below.

The WVOD executives would like to see a regression model
that predicts the amount of advertising sales based on the number of viewers
and the length of the program. Develop this regression model (“Regression Model
A”). Web Video on Demandwould like to acquire a 60-minute documentary special
about social media and bullying. The special is aimed at teen viewers and is
estimated to bring in 3.2 million viewers. Based on the regression model,
predict the advertising sales that could be generated by the special.

The WVOD executives would alsolike to see a regression model
that predicts the amount of advertising sales based on the number of viewers,
the length of the program, and the average viewer age. Develop this regression
model (“Regression Model B”). Web Video on Demandmay acquire a 2-hour film that
was a hit with critics and audiences at several international film festivals.
Initial customer surveys indicate that the film could bring in 14.1 viewers and
the average viewer age would be 32. Use this information to predict the
advertising sales.

Advertising Sales ($) Average # of Viewers (Millions) Length of Program (Minutes) Average Viewer Age (years)
28,000 10.1 30 30
25,500 11.4 30 25
31,000 19.9 60 30
29,000 13.6 60 38
20,500 12.5 60 20
14,500 3.5 30 15
27,000 15.1 60 24
23,500 3.7 30 17
19,500 4.3 30 19
23,000 12.2 120 45
18,000 5.1 120 19
29,500 15.9 60 28
30,000 16.8 120 31
25,000 8.5 120 58
22,500 9.1 30 43

 

 

GC BUS 660 week 5 Forecasting Case Study: Urban Planning
assignment

Details:

Review “Forecasting Case Study: Urban Planning”
for this topic’s case study, in which you will serve as an urban planner
forecasting economic growth and decline for a specific industry in your city.

Students must access the “County Business
Patterns” webpage (https://www.census.gov/econ/cbp/index.html)
for this assignment. Students will use this U.S. Census Industry data portal to
access data for a zip code with which you are familiar. This can be the zip
code of your personal residence, location of employer (corporate, regional, or
local office), undergraduate educational institution, hometown, etc.

In addition to the forecasting model and data, prepare a
500-750-word report to your city manager. Explain your approach and the
rationale for why this is the best model. Evaluate the data and conclude your
report with a recommendation about either expanding the industry in your area
or allocating resources elsewhere.

Use an Excel spreadsheet file for the calculations and
explanations. Cells should contain the formulas (i.e., if a formula was used to
calculate the entry in that cell). Students are highly encouraged to use the
“Forecasting Template” Excel resource to complete this assignment.

Mac users can use StatPlus:mac LE, free of charge, from
AnalystSoft.

Prepare the assignment according to the guidelines found in
the APA Style Guide, located in the Student Success Center. An abstract is not
required.

This assignment uses a rubric. Please review the rubric
prior to beginning the assignment to become familiar with the expectations for
successful completion.

You are required to submit this assignment to Turnitin.
Please refer to the directions in the Student Success Center.

Forecasting Case Study: Urban Planning

Important Note: Students must access the “County Business
Patterns” Topic Material for this assignment. Students will use this U.S.
Census Industry data portal to access data for a zip code with which you are
familiar. This can be the zip code of your personal residence, location of
employer (corporate, regional, or local office), undergraduate educational
institution, hometown, etc.

Scenario

You have recently been hired as an urban planner for your
local government. You have been tasked with determining economic growth and
decline patterns in your area. As an urban planner, you will ultimately be
responsible for determining patterns and forecasting for all industries within
your area. However, the city manager has asked that you prioritize one of the
10 industries below. Business proposals have been submitted and the city
manager would like to have use forecasting data to make an informed decision
about whether to approve industry expansion or to allocate resources elsewhere.

Industries

· Construction

· Manufacturing

· Transportation and Warehousing

· Information

· Finance and Insurance

· Real Estate and Rental and Leasing

· Professional, Scientific, and Technical Services

· Management of Companies and Enterprises

· Administrative and Support and Waste Management and
Remediation Services

· Health Care and Social Assistance

Forecasting

Access the “County Business Patterns” page on the United
States Census Bureauwebsite and enter your city’s zip code. Using one of the
industries above, access the data for the last 5 years that are available on
website. Determine patterns of economic growth or decline during this time
period, and develop the most optimal forecasting model for the next 2 years.
Note that you will need to set up these two forecast calculations.

Clearly justify why your selected model is the best one.
Specifically explain what forecast error is and how you used it to ascertain
the most optimal forecasting model. Assume that you are presenting your
findings to senior management and that senior management has minimal knowledge
of forecasting techniques and how forecast error is calculated.

GC BUS 660 week 6 Introduction to Optimization Modeling
Problem Set assignment

Details:

Manually complete the following problems in the textbook:

  1. Problem
    7-14
  2. Problem
    7-15
  3. Problem
    7-18

Use an Excel spreadsheet file for the calculations and
explanations. Cells should contain the formulas (i.e., if a formula was used to
calculate the entry in that cell). Students are highly encouraged to use the
“Optimization Modeling Problem Set” Excel resource to complete this
assignment.

Mac users can use StatPlus:mac LE, free of charge, from
AnalystSoft.

You are not required to submit this assignment to Turnitin.

 

 

GC BUS 660 week 7 Benchmark – Data Analysis Case Study
assignment

Details:

Review “Benchmark Assignment – Data Analysis Case
Study” and “Benchmark Assignment – Data Analysis Case Study
Data”for this topic’s case study, evaluating operations for a local
restaurant.

Although your friend and restauranteur Michael Tanaglia
offered to go over your findings in person, you believe it would be appropriate
to also prepare a report and document your findings in writing. In a
1,000-1,250-word report, explain your approach for each evaluation and the
rationale for the methods you used. Include any recommendations based on
customer satisfaction, forecasting, and staff scheduling data.

Use an Excel spreadsheet file for the calculations and
explanations. Cells should contain the formulas (i.e., if a formula was used to
calculate the entry in that cell). Students are highly encouraged to use the
“Benchmark Assignment – Data Analysis Case Study Template” and
“Benchmark Assignment – Data Analysis Case Study Linear Programming
Template” to complete this assignment.

Mac users can use StatPlus:mac LE, free of charge, from
AnalystSoft.

Prepare the assignment according to the guidelines found in
the APA Style Guide, located in the Student Success Center. An abstract is not
required.

This assignment uses a rubric. Please review the rubric
prior to beginning the assignment to become familiar with the expectations for
successful completion.

You are required to submit this assignment to Turnitin.
Please refer to the directions in the Student Success Center.

 

 

GC BUS 660 week 8 Simulation Case Study: Phoenix Boutique
Hotel Group assignment

Details:

Review “Simulation Case Study: Phoenix Boutique Hotel
Group” for this topic’s case study, in which you provide guidance to
Phoenix Boutique Hotel Group (PBHG) founder Bree Bristowe.

In addition to creating a simulation model, prepare a
500-750-word recommendation for Bristowe’s best course of action. Explain your
model and the rationale for your recommendations.

Use an Excel spreadsheet file for the calculations and
explanations. Cells should contain the formulas (i.e., if a formula was used to
calculate the entry in that cell). Students are highly encouraged to use the
“Simulation Case Study: Phoenix Boutique Hotel Group Template” Excel
resource to complete this assignment.

Mac users can use StatPlus:mac LE, free of charge, from
AnalystSoft.

Prepare the assignment according to the guidelines found in
the APA Style Guide, located in the Student Success Center. An abstract is not
required.

This assignment uses a rubric. Please review the rubric
prior to beginning the assignment to become familiar with the expectations for
successful completion.

You are required to submit this assignment to Turnitin.
Please refer to the directions in the Student Success Center.