Nonlinear regression with R
The aim of this course is to teach you how to analyse your data if there are complicated relationships between the variables. Please note that we cannot go into the specific data analysis problems of your particular project.
Instructor: András Aszódi.
Topics
- How to fit a PCR curve? Simple nonlinear regression.
- Did my enzyme inhibitor work? Statistical comparison of several nonlinear regression models.
- More than one independent variable? Multivariable nonlinear regression.
- Non-parametric techniques: LOESS, kernel smoothing methods, splines, generalized additive models.
Prerequisites
- Mandatory: Good understanding of basic statistics concepts. If you have attended our Think Statistics with R course, then you are all set.
- Recommended:
- Familiarity with linear regression. Our Linear Regression course gives you a solid overview.
- Basic familiarity with R. Our R as a programming language course provides you with the necessary knowledge.
Practical information
Number of participants: minimum 5, maximum 10.
Length: The course takes one half-day, from 09:00 to 13:00 with 2 breaks.