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Group Project – Predictive Model
Foundations of Predictive Analytics
& Decision Modeling
QNT 2020
Group Project on Predictive Models
Daniel Davidson
1-1
Understanding Franchise Performance
• Your boss wants your help to understand what drives the performance of
stores of the Subway franchise.
• Your boss helps you acquire data from last year’s sales and the
demographic factors of each store:
• SALES
• SQFT
• INVENTORY
• ADVERTISING
• FAMILIES
• STORES
• The EXCEL data file (Franchises.xlxs) has a data dictionary describing the
meaning of the variables.
Using Simple Linear Regression Models to Understand
Franchise Performance
• Use the dataset in Franchises.xlxs.
• Build a model to establish which individual factors affect sales in our
franchises and how?
• Can we create a model to help design a store and achieve a certain
level of sales?
• Which factors are critical to the design of the store: area (sq ft), inventory,
advertising spend, size of the sales district, number of competing stores?
Using SLR Analysis to Understand Franchise
Performance
• Examine the Bivariate Relationships
• How is the size of the customer base around each store related to our expected
sales?
• Use the data to determine the relationship between SALES and FAMILIES (the size of the
customer base around each store).
• Use the data to determine the relationship between SALES and SQFT (the area each
store occupies).
• Use the data to determine the relationship between SALES and Inventory (the
amount of items in each store).
• Use the data to determine the relationship between SALES and Advertising (the
amount of money each store spends on promotion).
• Use the data to determine the relationship between SALES and Stores (the number
of competing stores near by each store in our franchise).
• Use linear regression to build models to answer these questions.
Using SLR Analysis to Understand Franchise
Performance
• Perform the analysis and then give your answer to the question posed
above, with you reason for the answers.
• The EXCEL data file has a data dictionary describing the meaning of
the variables.
Using Multivariate Regression Models to Understand
Franchise Performance
• Use the same dataset in Franchises.xlxs.
• Build a model to answer the questions:
• Which collection of factors affect sales in our franchises and how?
• Can we create a model to design a store given certain demographics so we
can achieve a certain level of sales?
• Examine each of the variables and see if any variables need to be transformed to
improve the multi-variate model.
• Build a multivariate regression model that can be used to predict
store sales
Prediction Analysis
• Use the model to do some analysis.
• We just opened a store in a neighborhood with 5,000 families, the store is
5,000 sq ft, we are planning to spend $5,000 a month in advertising, carry
$250,000 in inventory and there are 5 competing stores in the neighborhood.
•
• What are the projected sales?
PROJECT REPORT GUIDELINES
• You can use the following outline for your project report:
• Introduction: introduce the problem, provide some background
• Problem Statement: describe the problem you are proposing to solve,
• State the assumptions (if any)
• Data Sources: list the sources of data you expect to extract data for developing the
analysis.
• Data Description: describe the data (explain any terms that are specific to
your dataset
• Methods: discuss your modelling approach, what are the independent
variables (co-variates), what is the dependent variable. Provide as much
detail about the various models you have in your study. Did you need to
transform any variables? How well do the variables fit the model? How well
do the variables describe the model?
• Results: what is the outcome of your analysis across the different models?
• Conclusion: Do you have a recommendation?
• Include tables and visuals to support your analysis.
• Your project report should be 5-7 pages.
PROJECT SUBMISSION DETAILS
• Please submit only one report for each group
• You can submit in either Word or PDF format
• Your group report is due by end of day November 4th.
• Please submit your report to the BB -> Group Project 1
Submission
• Only one report per group should be submitted.
• Also submit your EXCEL file showing all the models you have
developed (one model per worksheet tab).
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