Discrete Choice Modeling and Conjoint Analysis

This course will teach you to design appropriate conjoint and choice studies using surveys, panels, designed experiments, be able to analyze and interpret the resulting data.

Overview

Complex sample designs such as stratified cluster sampling make it possible to extract maximum information at minimum cost, but they are typically harder to work with than simple random samples. How do you analyze the resulting data – in particular, how do you determine margins of error? This course teaches you how to estimate variances when analyzing survey data from complex samples, and also how to fit linear and logistic regression models to complex sample survey data.

• 4 Weeks
• Expert Instructor
• Tuiton-Back Guarantee
• 100% Online
• TA Support

Learning Outcomes

Students who complete this course will learn fundamental concepts of conjoint analysis. Topics include: designing conjoint and choice studies; conjoint analysis of rank data; and introduction to the multinomial logit model.

• Design experiments to manipulate the appearance of attribute levels in product concepts.
• Use the resulting data to infer how the product attribute levels drive preference or choice.
• Fit a model to the data to predict how the market would choose among a set of competing product alternatives

Who Should Take This Course

Market researchers and consultants, analysts studying corporate strategy.

Course Syllabus

Week 1

Fundamental Concepts

• Ranks, ratings, choices
• Random utility models

Week 2

Designing Conjoint and Choice Studies

• Samples
• Surveys
• Panel data
• Criteria for obtaining better designs

Week 3

Conjoint Analysis of Rank Data

• Conjoint analysis of rank and ratings
• Conjoint simulation

Week 4

Introduction to the Multinomial Logit Model

• Multinomial logit model
• Maximum likelihood estimation
• Extensions to the basic model

Class Dates

2023

08/25/2023 to 09/22/2023
Instructors:

Prerequisites

Participants should have some familiarity with statistical modeling techniques (e.g. regression).

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Discrete Choice Modeling and Conjoint Analysis

Homework

Homework in this course consists of short answer questions to test concepts and guided data analysis problems using software.

Guided data modeling problems using software

In addition to assigned readings, this course also has Discussion tasks, and an end of course data modeling project.

Course Text

The course text is Applied Choice Analysis: A Primer by David A. Hensher, John M. Rose and William H. Greene, published by Cambridge Press.

Software

Examples of design and analysis will be shown in various software packages. While the course text is tuned to Nlogit/Limdepo, no software is required to do the coursework.

Course Fee & Information

Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout. Use promo code ACADEMIC where prompted during registration.

Invoice or Purchase Order
Add \$50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Literacy, Accessibility, and Dyslexia

At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:

Chrome

Firefox

Safari

• Navidys (for colorblindness, dyslexia, and reading difficulties)
• HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

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Discrete Choice Modeling and Conjoint Analysis