Dummy Variable Regression & Conjoint (Survey) Analysis in R

Explore powerful statistical techniques to understand and predict consumer behavior with this comprehensive course, covering both Dummy Variable Regression and Conjoint Analysis.

---

Dummy Variable Regression: Unveiling Hidden Relationships

This section dives deep into Dummy Variable Regression, a crucial tool for analyzing categorical data. You'll gain practical skills and theoretical understanding to:

• Understand the Need for Dummy Variables: Learn why and when to use dummy variables in your regression models.
• Dummy Variable Regression Demo & Interpretation: Get hands-on experience and learn to interpret the results of dummy variable regression models.
• Theory of Detecting Intercept & Slope Change: Master the theory behind identifying changes in intercepts and slopes within your regression analysis. Understand how to determine if only the intercept, only the slope, or both are changing.
• Detecting Slope Changes: Learn specific techniques to identify and interpret changes in the slope of your regression model.
• Real-World Applications: Discover two practical applications of Dummy Variable Regression:
  • Detecting Structural Breaks: Use dummy variables to identify significant shifts or changes in trends within your data.
  • Detecting Seasonality: Analyze seasonal patterns in your data using dummy variables.
• ANOVA & ANCOVA Models: Explore how Dummy Variable Regression relates to and enhances your understanding of ANOVA and ANCOVA models.

---

Conjoint Analysis: Understanding Customer Preferences

This part focuses on Conjoint Analysis, a powerful technique for understanding how consumers value different product features. You'll learn to:

• What is Conjoint Analysis?: Get a clear understanding of the principles and applications of Conjoint Analysis.
• Applying Conjoint Analysis: Learn how to effectively utilize Conjoint Analysis to gather valuable insights.
• Determining Attribute Importance: Discover methods to identify the relative importance of different product attributes to your target audience.
• Calculating Part Worth: Learn how to calculate the "part worth" of each attribute – how much value consumers place on each feature.
• Conjoint Design & Survey Analysis:
  • Designing Conjoint Analysis Surveys: Learn the best practices for designing effective Conjoint Analysis surveys.
  • Survey Result Analysis (Excel): Analyze Conjoint Analysis survey data using Excel.
  • Survey Result Analysis (R): Perform advanced analysis of Conjoint Analysis data using R.
• Real-World Validity: Understand how to validate the results of Conjoint Analysis and ensure they accurately reflect real-world consumer behavior.
• Advanced Conjoint Analysis: Explore advanced topics, including:
  • Fractional Factorial Design: Understand the need for and benefits of using fractional factorial designs in Conjoint Analysis.
  • Qualities of Fractional Factorial Design: Learn about balance and orthogonality in fractional factorial designs.
• Fractional Factorial Design with R:
  • Generating Fractional Factorial Designs (R): Use R to create fractional factorial designs.
  • Applying Designs with Sample Data (R): Implement and analyze fractional factorial designs using sample data in R.