Week 3
assignment
Simple Regression Models Case Study: Mystery Shoppers
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 website 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 vacation ? 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 statistically
significant 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
