Dummy Variable Regression & Conjoint (Survey) Analysis in R
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# Dummy Variable Regression & Conjoint (Survey) Analysis in R

Dummy Variable regression (ANOVA / ANCOVA / structural shift), Conjoint analysis for product design Survey analysis
4.0 (2 ratings)
18 students enrolled
Last updated 6/2017
English
Current price: \$12 Original price: \$20 Discount: 40% off
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Includes:
• 2 hours on-demand video
• 8 Supplemental Resources
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

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What Will I Learn?
• What is dummy variable regression? Why do you need it?
• How to detect various kind of possibilities (Just slope change, intercept change etc.)
• How to interpret dummy variable regression output?
• What is conjoint analysis? Why do you need it?
• How to do conjoint analysis using Excel?
• How to perform design of experiment for orthogonal and balanced fractional factorial design?
• How to use R for selection balance and orthogonal subset for fractional factorial design?
• How to use R for conjoint analysis?
• What is ANOVA & ANCOVA model?
View Curriculum
Requirements
• Basic of linear regression
• Basics of R programming (because the course will cover only conjoint related syntax)
• How to download resource files available
Description

This course has two parts. Part one refers to Dummy Variable Regression and part two refers to conjoint analysis.

Let me give you details of what you are going to get in each part.

---------------------------------

Part One - Dummy Variable Regression

--------------------------------

• Need of a dummy variable
• Demo and Interpretation of dummy variable regression
• Theory of detecting Intercept,  slope change etc. How to know, what kind of situation you have. Is is just
• intercept change,
• slope change or
• both Intercept and slope changing or
• nothing changing?
• Demo of detecting slope change etc
• Another two application of concepts of dummy variable regression
• Using dummy variable to detect structral break
• Using dummy variable to detect seasonality
• ANOVA n ANCOVA models

---------------------------------

Part Two - Conjoint Analysis

--------------------------------

• What is Conjoint Analysis
• Usage of conjoint analysis
• How do you know relative importance of attributes
• How do you know part worth
• Steps for designing Conjoint Analysis
• Survey Result analysis using Excel for Conjoint Study
• Survey Result analysis using R for Conjoint Study
• When Conjoint Analysis reflects real world phenomena and how will you know that it is holding true
• Advance conjoint analysis issues n approach
• why do you need fractional factorial design?
• qualities for fractional factorial design - balance and orthogonal
• Using R to get fractional factorial design
• Demo of fractional factorial design
• Using sample data of fractional factorial design in R

Who is the target audience?
• Market Research Professionals
• Analytics Professionals
• Analytics Students
Compare to Other Regression Analysis Courses
Curriculum For This Course
19 Lectures
01:53:39
+
Dummy Variable Regression - theory and demo
6 Lectures 32:00
Preview 00:51

Preview 01:23

Preview 05:04

Demo n Interpretation of dummy variable regression
12:38

How to know, what kind of situation you have. Is is just

• intercept change,
• slope change or
• both changing or
• nothing changing?
Theory of detecting Intercept, slope change etc
06:29

Demo of detecting Intercept, slope change etc
05:35
+
Advance usage of Dummy Variable regression
3 Lectures 10:20
Preview 04:28

Using dummy variable to detect seasonality
02:35

ANOVA n ANCOVA models
03:17
+
Conjoint Analysis
6 Lectures 43:46
Preview 00:59

What is Conjoint Analysis?
05:08

-How do you know relative importance of attributes
-How do you know part worth

Usage of conjoint analysis
05:49

Steps for designing Conjoint Analysis
07:34

Survey Result analysis using Excel for Conjoint Study
11:03

Survey Result analysis using R for Conjoint Study
13:13
+
Advance Topic of conjoint analysis & fractional factorial design
4 Lectures 27:33

How will you know that your analysis is working?

When Conjoint Analysis reflects real world phenomena?
06:49

• why do you need fractional factorial design?
• qualities for fractional factorial design - balance and orthogonal

Advance conjoint analysis issues n approach
10:54

Using R to get fractional factorial design
08:20

Closing Note
01:30