- Data Analysis
- Data Ethics
- Predictive Modeling
- Regression Analysis
- Probability Distribution
- Statistical Modeling
- Statistical Inference
- Classification And Regression Tree (CART)
- Machine Learning
- Calculus
- Statistical Methods
- Linear Algebra
Generalized Linear Models and Nonparametric Regression
Completed by David Geller III
January 10, 2024
42 hours (approximately)
David Geller III'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
