Dummy Variable Regression & Conjoint (Survey) Analysis in R

Dummy Variable regression (ANOVA / ANCOVA / structural shift), Conjoint analysis for product design Survey analysis

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.

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Part One - Dummy Variable Regression

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• 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

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Part Two - Conjoint Analysis

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• 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