About this Course
The second course in the program presents methods and strategies for developing both simple and complex models in R, allowing you to analyze relationships in multivariate data. We’ll explore how to measure the models’ fit, establish confidence intervals on the model parameters, identify outlier data, and understand what the model parameters represent. At the conclusion of the course, you’ll be able to develop programs in R to measure, analyze and display how well the models represent complex data, as well as be able to interpret and report on the results.
What You’ll Learn
- Strategies for choosing appropriate models to best answer a given scientific question
- How to interpret and graphically display and report the results
- Aspects of multiple linear regression
- Techniques for analyzing Analysis of Covariance, 1- and 2-way ANOVA
- Details about data transformations, dummy variables and outlier detection
Get Hands-On Experience
You’ll complete a data analysis project using real-world examples to manipulate data, display and report results, and draw appropriate conclusions.