University of Colorado Boulder - Regression Modeling for Marketers
- Offered byCoursera
Regression Modeling for Marketers at Coursera Overview
Duration | 19 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course |
Credential | Certificate |
Regression Modeling for Marketers at Coursera Highlights
- Earn a certificate from Coursera
- Learn from industry experts
Regression Modeling for Marketers at Coursera Course details
- Apply regression analysis to understand & predict marketing outcomes
- Interpret market data & refine statistical models for real-world application
- "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
Regression Modeling for Marketers at Coursera Curriculum
Understanding Simple Linear Regression
The Main Ideas of Simple Linear Regression (SLR)
Describing Lines and Normal Distributions
Residuals, SSE, and Ordinary Least Squares Regression
Confidence Bands for Regression Lines: Homoscedasticity
Predicting With SLR: Obtaining Regression Coefficients
A Note About Readings & R-Scripts
Simple Linear Regression
R-Scripts - Simple Linear Regression (SLR), Normal Distribution, and Prediction Intervals
The Main Ideas of Simple Linear Regression (SLR) Quiz
Describing Lines and Normal Distributions Quiz
Residuals, SSE, and Ordinary Least Squares Regression Quiz
Confidence Bands for Regression Lines: Homoscedasticity Quiz
Predicting With SLR: Obtaining Regression Coefficients Quiz
Module 1 Graded Quiz
Interpreting SLR Output
Testing for Normality of Residuals
Standard Errors for Regression Coefficients
R-Squared
Summary of Regression Outputs
Difference of Means, Part 1: Two-Sample T-Test
Difference of Means, Part 2: SLR with Dummy Variables and A/B Testing
Q-Q Plots
R-Scripts - SLR & Q-Q Plots
Adjusted R-Squared
AB Testing
Testing for Normality of Residuals Quiz
Standard Errors for Regression Coefficients Quiz
R-Squared Quiz
Summary of Regression Outputs Quiz
Difference of Means, Part 1: Two-Sample T-Test Quiz
Difference of Means, Part 2: SLR with Dummy Variables and A/B Testing Quiz
Module 2 Graded Quiz
Beyond Simple Linear Regression (SLR)
Checking SLR Assumptions
Assessing SLR Assumptions Visually: Anscombe's Quartet
Non-Parametric Smoothing Regression Using LOESS: Part 1
Non-Parametric Smoothing Regression Using LOESS: Part 2
Comparing SLR and LOESS
Introduction to Multiple Linear Regression (MLR)
R-Squared for MLR
MLR with Discrete Independent Variables: One-Hot Encoding
Interpreting MLR Coefficients for Dummy Variables
Wrap-up on One-Hot Encoding in MLR
R-Scripts - SLR & Comparing Prediction Intervals
Non-Parametric Smoothing Regression
R-Scripts - Smoothing Regression LOESS
Multiple Linear Regression (MLR)
R-Scripts - Multiple Linear Regression (MLR)
One-Hot Encoding with 0-1 Dummy Variables
Checking SLR Assumptions Quiz
Assessing SLR Assumptions Visually: Anscombe's Quartet Quiz
Non-Parametric Smoothing Regression Using LOESS: Part 1 Quiz
Non-Parametric Smoothing Regression Using LOESS: Part 2 Quiz
Comparing SLR and LOESS Quiz
Introduction to Multiple Linear Regression (MLR) Quiz
R-Squared for MLR Quiz
MLR with Discrete Independent Variables: One-Hot Encoding Quiz
Interpreting MLR Coefficients for Dummy Variables Quiz
Wrap-up on One-Hot Encoding in MLR Quiz
Module 3 Graded Quiz
Applying and Generalizing Multiple Linear Regression (MLR)
Analysis of Variance (ANOVA)
Checking Anova Assumptions
Analysis of Covariance (ANCOVA)
Beyond ANCOVA
Logistic Regression & Generalized Linear Models
MLE and Multivariate Logistic Regression
Causal Evaluation with Regression Models 1: Improved A/B Testing with MLR
Causal Evaluation with Regression Models 2: Multivariate Testing and Uplift Modeling
Causal Evaluation with Regression Models 3: Difference-in-Differences (DID)
Causal Evaluation Methods
Analysis of Variance (ANOVA)
R-Scripts - Analysis of Variance (ANOVA) and Beyond
Kruskal-Wallis Non-Parametric ANOVA
ANCOVA & Multicollinearity Testing and VIF Factors
MANOVA & Stepwise Variable Selection
Logistic Regression and Generalized Linear Models
R-Scripts - Logistic Regression
Multinomial Logistic Regression and GAM
A/B Testing
Multivariate Testing & Uplift Modeling
Difference-in-Differences (DID)
Analysis of Variance (ANOVA) Quiz
Checking Anova Assumptions Quiz
Analysis of Covariance (ANCOVA) Quiz
Beyond ANCOVA Quiz
Logistic Regression & Generalized Linear Models Quiz
MLE and Multivariate Logistic Regression Quiz
Causal Evaluation with Regression Models 1: Improved A/B Testing with MLR Quiz
Causal Evaluation with Regression Models 2: Multivariate Testing and Uplift Modeling Quiz
Causal Evaluation with Regression Models 3: Difference-in-Differences (DID) Quiz
Causal Evaluation Methods Quiz
Module 4 Graded Quiz