Regression Modeling for Marketers

Regression Modeling for Marketers

This course is part of Data Science for Marketing Specialization

Instructors: A.W. Lukens

What you'll learn

Apply regression analysis to understand & predict marketing outcomes. Interpret market data & refine statistical models for real-world application.

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Assessments

35 assignments

Taught in English

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This course is part of the Data Science for Marketing Specialization

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There are 4 modules in this course

"Regression Modeling for Marketers" is a specialized course designed to elevate marketing professionals' analytical skills. Focusing on regression analysis, the course enables learners to quantify, explain, and predict marketing outcomes using both simple and multiple linear regression models. This course stands out by not only teaching the creation and interpretation of market data visualizations but also showing the use of advanced statistical software for gaining marketing insights. Learners will explore sophisticated analytical techniques like ANOVA, ANCOVA, and MANCOVA, enhancing their ability to dissect the impact of marketing strategies. The course also covers logistic regression and multivariate testing, key tools for anticipating market shifts and consumer choices. Additionally, it emphasizes the application of uplift modeling for targeted and personalized marketing campaigns, making it an essential resource for contemporary marketers.

Grasp the essentials of Simple Linear Regression to predict and influence market outcomes. This module guides you through creating insightful scatter plots and using statistical software, turning data into reliable, predictive tools for marketing success.

What's included

5 videos3 readings6 assignments

5 videosTotal 18 minutes

The Main Ideas of Simple Linear Regression (SLR)4 minutesPreview module
Describing Lines and Normal Distributions2 minutes
Residuals, SSE, and Ordinary Least Squares Regression4 minutes
Confidence Bands for Regression Lines: Homoscedasticity3 minutes
Predicting With SLR: Obtaining Regression Coefficients4 minutes

3 readingsTotal 41 minutes

A Note About Readings & R-Scripts1 minute
Simple Linear Regression30 minutes
R-Scripts - Simple Linear Regression (SLR), Normal Distribution, and Prediction Intervals10 minutes

6 assignmentsTotal 102 minutes

Module 1 Graded Quiz30 minutes
The Main Ideas of Simple Linear Regression (SLR) Quiz15 minutes
Describing Lines and Normal Distributions Quiz15 minutes
Residuals, SSE, and Ordinary Least Squares Regression Quiz15 minutes
Confidence Bands for Regression Lines: Homoscedasticity Quiz12 minutes
Predicting With SLR: Obtaining Regression Coefficients Quiz15 minutes

Learn to decode SLR outputs, enhancing your ability to make precise marketing predictions. Understand the significance of regression coefficients and R-squared values in shaping marketing strategies that are both data-driven and impactful.

What's included

6 videos4 readings7 assignments

6 videosTotal 24 minutes

Testing for Normality of Residuals4 minutesPreview module
Standard Errors for Regression Coefficients5 minutes
R-Squared3 minutes
Summary of Regression Outputs2 minutes
Difference of Means, Part 1: Two-Sample T-Test3 minutes
Difference of Means, Part 2: SLR with Dummy Variables and A/B Testing5 minutes

4 readingsTotal 80 minutes

Q-Q Plots30 minutes
R-Scripts - SLR & Q-Q Plots10 minutes
Adjusted R-Squared10 minutes
AB Testing30 minutes

7 assignmentsTotal 123 minutes

Module 2 Graded Quiz30 minutes
Testing for Normality of Residuals Quiz15 minutes
Standard Errors for Regression Coefficients Quiz18 minutes
R-Squared Quiz15 minutes
Summary of Regression Outputs Quiz15 minutes
Difference of Means, Part 1: Two-Sample T-Test Quiz15 minutes
Difference of Means, Part 2: SLR with Dummy Variables and A/B Testing Quiz15 minutes

Elevate your predictive modeling with advanced techniques. This module takes you beyond SLR, showing you how to incorporate multiple factors into your analyses for more nuanced and effective marketing insights.

What's included

10 videos6 readings11 assignments

10 videosTotal 36 minutes

Checking SLR Assumptions2 minutesPreview module
Assessing SLR Assumptions Visually: Anscombe's Quartet2 minutes
Non-Parametric Smoothing Regression Using LOESS: Part 12 minutes
Non-Parametric Smoothing Regression Using LOESS: Part 23 minutes
Comparing SLR and LOESS3 minutes
Introduction to Multiple Linear Regression (MLR)2 minutes
R-Squared for MLR3 minutes
MLR with Discrete Independent Variables: One-Hot Encoding5 minutes
Interpreting MLR Coefficients for Dummy Variables5 minutes
Wrap-up on One-Hot Encoding in MLR2 minutes

6 readingsTotal 70 minutes

R-Scripts - SLR & Comparing Prediction Intervals10 minutes
Non-Parametric Smoothing Regression10 minutes
R-Scripts - Smoothing Regression LOESS10 minutes
Multiple Linear Regression (MLR)10 minutes
R-Scripts - Multiple Linear Regression (MLR)10 minutes
One-Hot Encoding with 0-1 Dummy Variables20 minutes

11 assignmentsTotal 171 minutes

Module 3 Graded Quiz30 minutes
Checking SLR Assumptions Quiz15 minutes
Assessing SLR Assumptions Visually: Anscombe's Quartet Quiz15 minutes
Non-Parametric Smoothing Regression Using LOESS: Part 1 Quiz15 minutes
Non-Parametric Smoothing Regression Using LOESS: Part 2 Quiz12 minutes
Comparing SLR and LOESS Quiz12 minutes
Introduction to Multiple Linear Regression (MLR) Quiz15 minutes
R-Squared for MLR Quiz12 minutes
MLR with Discrete Independent Variables: One-Hot Encoding Quiz15 minutes
Interpreting MLR Coefficients for Dummy Variables Quiz15 minutes
Wrap-up on One-Hot Encoding in MLR Quiz15 minutes

Discover the power of Multiple Linear Regression in understanding complex market dynamics. Learn to integrate diverse factors into your analysis, using advanced techniques like ANOVA and MANCOVA for deeper market insights and smarter marketing decisions.

What's included

10 videos11 readings11 assignments

10 videosTotal 46 minutes

Analysis of Variance (ANOVA)5 minutesPreview module
Checking Anova Assumptions2 minutes
Analysis of Covariance (ANCOVA)5 minutes
Beyond ANCOVA3 minutes
Logistic Regression & Generalized Linear Models3 minutes
MLE and Multivariate Logistic Regression8 minutes
Causal Evaluation with Regression Models 1: Improved A/B Testing with MLR3 minutes
Causal Evaluation with Regression Models 2: Multivariate Testing and Uplift Modeling4 minutes
Causal Evaluation with Regression Models 3: Difference-in-Differences (DID)5 minutes
Causal Evaluation Methods3 minutes

11 readingsTotal 255 minutes

Analysis of Variance (ANOVA)10 minutes
R-Scripts - Analysis of Variance (ANOVA) and Beyond10 minutes
Kruskal-Wallis Non-Parametric ANOVA10 minutes
ANCOVA & Multicollinearity Testing and VIF Factors45 minutes
MANOVA & Stepwise Variable Selection30 minutes
Logistic Regression and Generalized Linear Models30 minutes
R-Scripts - Logistic Regression10 minutes
Multinomial Logistic Regression and GAM40 minutes
A/B Testing10 minutes
Multivariate Testing & Uplift Modeling30 minutes
Difference-in-Differences (DID)30 minutes

11 assignmentsTotal 180 minutes

Module 4 Graded Quiz30 minutes
Analysis of Variance (ANOVA) Quiz15 minutes
Checking Anova Assumptions Quiz15 minutes
Analysis of Covariance (ANCOVA) Quiz15 minutes
Beyond ANCOVA Quiz15 minutes
Logistic Regression & Generalized Linear Models Quiz12 minutes
MLE and Multivariate Logistic Regression Quiz18 minutes
Causal Evaluation with Regression Models 1: Improved A/B Testing with MLR Quiz15 minutes
Causal Evaluation with Regression Models 2: Multivariate Testing and Uplift Modeling Quiz 15 minutes
Causal Evaluation with Regression Models 3: Difference-in-Differences (DID) Quiz15 minutes
Causal Evaluation Methods Quiz15 minutes