The University of Sydney Page 1
MKTG2113
Marketing Insight
Dr. Aekyoung (Amy) Kim
Copyright 2017 Pearson Education, Inc. 12-2
Multivariate Analysis I
LEARNING OBJECTIVES
The nature of logistic regression
analysis
How to test logistic regression
analysis using SPSS
How to report logistic regression
analysis findings
Outline
Characters of Logistic Regression
Use of Logistic Regression
Types of Logistic Regression Analysis
Bivariate logistic regression
Multiple logistic regression
Understanding Logistic Regression Model
Example of Logistic Regression Analysis
SPSS Exercise
3
When Is Logistic Regression Used
An extension of regression
What is different from regression
Same types of independent variable (IV) of regression
analysis (interval or ratio)
However, the dependent variable (DV) has only two
categories
Characters of Logistic Regression
Relationship between one or more IVs and a binary DV(e.g., two
categories)
Example DV:
Yes vs. No
True vs. False
Success vs. Failure
Buy vs. Not Buy
Response vs. No Response
Visit vs. Not Visit
Estimating the probability of an event taking place, such as the
probability of product purchase, a team winning, of a patient being
healthy, etc. (only between 0 and 1)
Use of Logistic Regression
A catalog company wants to increase the proportion of mailings that
result in sales (buy or not buy)
The catalog company can send mailings to the people who are
more likely to respond
A doctor wants to accurately diagnose a possibly cancerous tumor
The doctor can determine whether tumor is more likely to
benign or malignant
A loan officer wants to know wh
ether the next customer is likely to
default
The loan officer can assess the risk of extending credit to a
particular customer
Types of Logistic Regression Analysis
Bivariate regression (simple logistic
regression): having only one independent
variable to predict a dependent variable
(e.g., Can likeability of donation be
predicted by annual income )
Multiple logistic regression: having two
or more independent variables to predict a
dependent variable (e.g., Can likeability of
donation be predicted by a combination of
age, annual income, gender, and
perceived empathy )
7
IV1
IV2
IV3
IVn
DV
IV DV
Brainstorm 10-1
Think about a situation that you can use a bivariate or multiple logistic
regression.
State the IV(s) and DV respectively.
IV: interval or ratio variable
DV: A nominal variable with only two categories
Quiz!
Q1. Which question can be answered by a logistic regression analysis
I. Can we predict the number of returning to prison for a similar offence based on the
variables socio-economic status, gender, post-release counselling follow-ups, and length
of sentence
II. Is the likelihood of successful cancer treatment influenced by factors such as family
support, age of onset, and locus of control
III. Can I predict the probability of a person having a gym membership based on age,
gender, and whether or not they use a photo-blogging app on their phone
a. I and II
b. I and III
c. II and III
d. I, II, and III
How Can We Analyze These Data
Age CD Age CD Age CD
22 0 40 0 54 0
23 0 41 1 55 1
24 0 46 0 58 1
27 0 47 0 60 1
28 0 48 0 60 0
30 0 49 1 62 1
30 0 49 0 65 1
32 0 50 1 67 1
33 0 51 0 71 1
35 1 51 1 77 1
38 0 52 0 81 1