Regression Modeling for Marketers

Regression Modeling for Marketers

This course is part of Data Science for Marketing Specialization

Instructors: A.W. Lukens

Access provided by Collegial

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

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

Skills you'll gain

Tools you'll learn

Statistical Software

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

35 assignments

Taught in English

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This course is part of the Data Science for Marketing Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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Develop job-relevant skills with hands-on projects
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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 videos Total 19 minutes

The Main Ideas of Simple Linear Regression (SLR) 4 minutes
Describing Lines and Normal Distributions 3 minutes
Residuals, SSE, and Ordinary Least Squares Regression 5 minutes
Confidence Bands for Regression Lines: Homoscedasticity 3 minutes
Predicting With SLR: Obtaining Regression Coefficients 4 minutes

3 readings Total 41 minutes

A Note About Readings & R-Scripts 1 minute
Simple Linear Regression 30 minutes
R-Scripts - Simple Linear Regression (SLR), Normal Distribution, and Prediction Intervals 10 minutes

6 assignments Total 102 minutes

The Main Ideas of Simple Linear Regression (SLR) Quiz 15 minutes
Describing Lines and Normal Distributions Quiz 15 minutes
Residuals, SSE, and Ordinary Least Squares Regression Quiz 15 minutes
Confidence Bands for Regression Lines: Homoscedasticity Quiz 12 minutes
Predicting With SLR: Obtaining Regression Coefficients Quiz 15 minutes
Module 1 Graded Quiz 30 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 videos Total 25 minutes

Testing for Normality of Residuals 5 minutes
Standard Errors for Regression Coefficients 6 minutes
R-Squared 4 minutes
Summary of Regression Outputs 2 minutes
Difference of Means, Part 1: Two-Sample T-Test 3 minutes
Difference of Means, Part 2: SLR with Dummy Variables and A/B Testing 5 minutes

4 readings Total 80 minutes

Q-Q Plots 30 minutes
R-Scripts - SLR & Q-Q Plots 10 minutes
Adjusted R-Squared 10 minutes
AB Testing 30 minutes

7 assignments Total 123 minutes

Testing for Normality of Residuals Quiz 15 minutes
Standard Errors for Regression Coefficients Quiz 18 minutes
R-Squared Quiz 15 minutes
Summary of Regression Outputs Quiz 15 minutes
Difference of Means, Part 1: Two-Sample T-Test Quiz 15 minutes
Difference of Means, Part 2: SLR with Dummy Variables and A/B Testing Quiz 15 minutes
Module 2 Graded Quiz 30 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 videos Total 36 minutes

Checking SLR Assumptions 3 minutes
Assessing SLR Assumptions Visually: Anscombe's Quartet 3 minutes
Non-Parametric Smoothing Regression Using LOESS: Part 1 3 minutes
Non-Parametric Smoothing Regression Using LOESS: Part 2 4 minutes
Comparing SLR and LOESS 4 minutes
Introduction to Multiple Linear Regression (MLR) 3 minutes
R-Squared for MLR 4 minutes
MLR with Discrete Independent Variables: One-Hot Encoding 5 minutes
Interpreting MLR Coefficients for Dummy Variables 5 minutes
Wrap-up on One-Hot Encoding in MLR 3 minutes

6 readings Total 70 minutes

R-Scripts - SLR & Comparing Prediction Intervals 10 minutes
Non-Parametric Smoothing Regression 10 minutes
R-Scripts - Smoothing Regression LOESS 10 minutes
Multiple Linear Regression (MLR) 10 minutes
R-Scripts - Multiple Linear Regression (MLR) 10 minutes
One-Hot Encoding with 0-1 Dummy Variables 20 minutes

11 assignments Total 171 minutes

Checking SLR Assumptions Quiz 15 minutes
Assessing SLR Assumptions Visually: Anscombe's Quartet Quiz 15 minutes
Non-Parametric Smoothing Regression Using LOESS: Part 1 Quiz 15 minutes
Non-Parametric Smoothing Regression Using LOESS: Part 2 Quiz 12 minutes
Comparing SLR and LOESS Quiz 12 minutes
Introduction to Multiple Linear Regression (MLR) Quiz 15 minutes
R-Squared for MLR Quiz 12 minutes
MLR with Discrete Independent Variables: One-Hot Encoding Quiz 15 minutes
Interpreting MLR Coefficients for Dummy Variables Quiz 15 minutes
Wrap-up on One-Hot Encoding in MLR Quiz 15 minutes
Module 3 Graded Quiz 30 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 videos Total 47 minutes

Analysis of Variance (ANOVA) 6 minutes
Checking Anova Assumptions 3 minutes
Analysis of Covariance (ANCOVA) 5 minutes
Beyond ANCOVA 4 minutes
Logistic Regression & Generalized Linear Models 4 minutes
MLE and Multivariate Logistic Regression 9 minutes
Causal Evaluation with Regression Models 1: Improved A/B Testing with MLR 4 minutes
Causal Evaluation with Regression Models 2: Multivariate Testing and Uplift Modeling 4 minutes
Causal Evaluation with Regression Models 3: Difference-in-Differences (DID) 6 minutes
Causal Evaluation Methods 4 minutes

11 readings Total 255 minutes

Analysis of Variance (ANOVA) 10 minutes
R-Scripts - Analysis of Variance (ANOVA) and Beyond 10 minutes
Kruskal-Wallis Non-Parametric ANOVA 10 minutes
ANCOVA & Multicollinearity Testing and VIF Factors 45 minutes
MANOVA & Stepwise Variable Selection 30 minutes
Logistic Regression and Generalized Linear Models 30 minutes
R-Scripts - Logistic Regression 10 minutes
Multinomial Logistic Regression and GAM 40 minutes
A/B Testing 10 minutes
Multivariate Testing & Uplift Modeling 30 minutes
Difference-in-Differences (DID) 30 minutes

11 assignments Total 180 minutes

Analysis of Variance (ANOVA) Quiz 15 minutes
Checking Anova Assumptions Quiz 15 minutes
Analysis of Covariance (ANCOVA) Quiz 15 minutes
Beyond ANCOVA Quiz 15 minutes
Logistic Regression & Generalized Linear Models Quiz 12 minutes
MLE and Multivariate Logistic Regression Quiz 18 minutes
Causal Evaluation with Regression Models 1: Improved A/B Testing with MLR Quiz 15 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) Quiz 15 minutes
Causal Evaluation Methods Quiz 15 minutes
Module 4 Graded Quiz 30 minutes