- Logistic Regression
- R Programming
- Data Ethics
- Linear Algebra
- Calculus
- Statistical Inference
- Statistical Modeling
- Probability Distribution
- Regression Analysis
- Data Analysis
- Model Evaluation
- Predictive Modeling
Generalized Linear Models and Nonparametric Regression
Completed by Christopher Overton
July 5, 2025
42 hours (approximately)
Christopher Overton's account is verified. Coursera certifies their successful completion of Generalized Linear Models and Nonparametric Regression
What you will learn
Describe how to generalize the linear model framework to accommodate data that is not suitable for the standard linear regression model.
State some advantages and disadvantages of (generalized) additive models.
Describe how an additive model can be generalized to incorporate non-normal response variables (i.e., define a generalized additive model).
Skills you will gain
