Dummy Variable Regression Conjoint (Survey) Analysis in R

Dummy Variable Regression & Conjoint (Survey) Analysis in R, available at $24.99, has an average rating of 3.6, with 19 lectures, based on 31 reviews, and has 197 subscribers.

You will learn about 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? This course is ideal for individuals who are Market Research Professionals or Analytics Professionals or Analytics Students It is particularly useful for Market Research Professionals or Analytics Professionals or Analytics Students.

Enroll now: Dummy Variable Regression & Conjoint (Survey) Analysis in R

Summary

Title: Dummy Variable Regression & Conjoint (Survey) Analysis in R

Price: $24.99

Average Rating: 3.6

Number of Lectures: 19

Number of Published Lectures: 19

Number of Curriculum Items: 19

Number of Published Curriculum Objects: 19

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will 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?

Who Should Attend

Market Research Professionals

Analytics Professionals

Analytics Students

Target Audiences

Market Research Professionals

Analytics Professionals

Analytics Students

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

Course Curriculum

Chapter 1: Dummy Variable Regression – theory and demo

Lecture 1: Overview of the section content

Lecture 2: How to study this course?

Lecture 3: Background – What is the need of a dummy variable?

Lecture 4: Demo n Interpretation of dummy variable regression

Lecture 5: Theory of detecting Intercept, slope change etc

Lecture 6: Demo of detecting Intercept, slope change etc

Chapter 2: Advance usage of Dummy Variable regression

Lecture 1: Using dummy variable to detect structral break

Lecture 2: Using dummy variable to detect seasonality

Lecture 3: ANOVA n ANCOVA models

Chapter 3: Conjoint Analysis

Lecture 1: Section Overview

Lecture 2: What is Conjoint Analysis?

Lecture 3: Usage of conjoint analysis

Lecture 4: Steps for designing Conjoint Analysis

Lecture 5: Survey Result analysis using Excel for Conjoint Study

Lecture 6: Survey Result analysis using R for Conjoint Study

Chapter 4: Advance Topic of conjoint analysis & fractional factorial design

Lecture 1: When Conjoint Analysis reflects real world phenomena?

Lecture 2: Advance conjoint analysis issues n approach

Lecture 3: Using R to get fractional factorial design

Lecture 4: Closing Note

Instructors

Gopal Prasad Malakar
Trains Industry Practices on data science / machine learning

Rating Distribution

1 stars: 3 votes

2 stars: 2 votes

3 stars: 6 votes

4 stars: 13 votes

5 stars: 7 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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