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DAT 220 Module Five Exercise Six Guidelines and Rubric   Overview Bubba Gump Shrimp Company is a successful retailer of regional food, both in its restaurants and through other retail channels

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DAT 220 Module Five Exercise Six Guidelines and Rubric  

Overview

Bubba Gump Shrimp Company is a successful retailer of regional food, both in its restaurants and through other retail channels. Bubba Gump began as a small, privately-owned restaurant. Thanks to unexpected exposure from a blockbuster movie, Bubba Gump grew rapidly from its humble beginnings and now operates several restaurants, sells branded merchandise through an online retail site, and wholesales its branded merchandise to other retail outlets. Bubba Gump’s growth was initially very rapid in response to a strong demand and high name recognition that followed from its movie exposure. After its first few years of rapid growth, sales increased at slower rates and finally leveled off. Sales have declined in each of the last two years.

 

Your Assignment

Your task is to analyze the responses to the Bubba Gump Shrimp Company customer survey to better understand whether there is an opportunity to entice more customers to shop at the company’s web store. To address this business question, you will perform several types of analytic and pre-analytic processing against the customer sample data. You will need to address any data quality issues identified in Exercise 2, prepare the data for best use to address the business question, identify natural “clusters” within Bubba Gump’s customer population, and fit regression models that predict which customers are likely to shop at the web channel and how much they are likely to spend.

 

Using JMP, analyze the customer sample survey data for patterns and associations that address the defined business problem. 

 

Specifically, apply the following data mining methods to the survey data:

 

• Generate hierarchical clustering results using the Bubba Gump survey data as inputs.  o How many “natural” clusters does the JMP algorithm suggest exist in the data?

o Is there a difference in web channel activity across the clusters?

• Again using JMP, generate a regression model that explains web channel expenditure as a function of various customer characteristics that are measured in the data set. 
• Next, generate a logistic regression model using JMP that predicts whether a customer will make a purchase from the web channel. 
• Prepare a summary report that presents the results of each analysis and describes their implications for the business question at hand.

 

Guidelines

Assignment must follow these formatting guidelines: double spacing, 12-point Times New Roman font, one-inch margins, and APA citations. Page length requirements: 2–3 pages. 

 

               

 

 

 

Rubric

 

Critical Elements	Exemplary (100%)	Proficient (85%)	Needs Improvement (55%)	Not Evident (0%)	Value
Cluster Analysis	Meets “Proficient” criteria, and the results are related back to the defined business problem	Hierarchical clustering results are identified. The number of “natural” clusters is identified from the analysis	Hierarchical clustering results are identified. The number of “natural” clusters is not identified from the analysis, nor are the results related back to the defined business problem	No hierarchical clustering results are reported	35
Linear Regression	Meets “Proficient” criteria, and the results are related back to the defined business problem	Linear regression results from JMP are reported. Model specification is explained	Linear regression results from JMP are reported	No linear regression results are reported	30
Logistic Regression	Meets “Proficient” criteria, and the results are related back to the defined business problem	Logistic regression results from JMP are reported. Model specification is explained	Logistic regression results from JMP are reported	No logistic regression results are reported	35
				Earned Total	100%