BUS 660 Quantitative Methods all week discussions and assignments
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GCU BUS660 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.
GCU BUS660 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?
GCU BUS660 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?
GCU BUS660 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.
GCU BUS660 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?
GCU BUS660 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.
GCU BUS660 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.
GCU BUS660 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.
GCU BUS660 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.
GCU BUS660 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.
1. A $500 session that
can be scheduled at any time with TeachBest Consulting.
2.
2. A $750 session
offered monthly by an external employee development firm.
3.
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.
GCU BUS660 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:.analystsoft.com/en/products/statplusmacle/”>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
GCU BUS660 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
|
||
GCU BUS660 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
(.census.gov/econ/cbp/index.html”>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.
GCU BUS660 week 6
Introduction to Optimization Modeling Problem Set assignment
Details:
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.
GCU BUS660 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.
GCU BUS660 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.
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