UTILIZED THE BIG GROCERY REGRESSION RESULTS TEMPLATE, AND BIG GROCERY SURVEY DAT

UTILIZED THE BIG GROCERY REGRESSION RESULTS TEMPLATE, AND BIG GROCERY SURVEY DATA GROCERY STUDENT TO COMPLETE THIS ASSIGNMENT. UTILIZED THE EXAMPLES ON HOW THIS FINAL ASSIGNMENT IS SUPPOSED TO LOOK LIKE.
Multiple Linear Regression (with Survey Data)
This module is about using multiple linear regression with data that is captured using common survey
techniques. We will first introduce the problems associated with survey data then explore how we
can use the multiple linear regression model to investigate and analyze common survey data.
Module Objectives:
1. Introduce common survey data issues that arise with multiple linear regression analysis. (Part
1)
2. Introduce/justify some ways of analyzing data that has common survey data issues. (Part 2)
3. Give the student an opportunity to use multiple Linear regression in an application that
involves the issues introduced in Part 1. (part 3)
Again, the student will need to be able to perform a multiple linear regression as we did in previous
modules. This section will also require that some data is transformed from qualitative data to
quantitative data in a way that the data can be used in regression analysis.
Our main goal will be to understand some of the common problems associated with survey data. For the
purposes of this class we will define survey data as data that includes some subjective measures of “like”
or “satisfaction”. For example, one of the questions on the course perception survey that the student
will see at the completion of this course is:
“This course gave me a better understanding of this topic.”
The responses for this type of question are usually delineated as a set of categories or given on a Likert
scale (e.g. an arbitrary scale of 1 to 5). In the course perception survey, the possible responses for this
question are:
“Strongly Disagree”
“Disagree”
“Neutral”
“Agree”
“Strongly Agree”
The responder is guided towards choosing one of the possible responses.
As we have seen so far in this course, the goal of MLR it so tease out useful information from the data in
the form of correlation. This section is about how to go about getting useful information from these
“survey-type” questions to use in a meaningful way.
The format for this module is similar to previous modules.
Below is the outline of this module. The module will be broken into 3 parts. These are described below
and you need to tackle them in order (i.e. part 1 then part 2, …).
Multiple Linear Regression (with Survey Data)
Part 1. Introduction to linear regression and survey data
This part will introduce a problem facing Big Grocery as part of their expansion. Particularly, we
introduce some data which was collected from a survey which we need to use to help guide our
decision on where to build a new store.
Part 2: Survey data problems and solutions
This part will delve into the concept of survey data with an eye towards how linear regression
can be used to make inferences.
Part 3: Assessment Project
You will be given examples of analysis and you will asked to apply what you have learned in this
module to the problem introduced in Part 1 and submit your work as a graded deliverable.