Solution: Explore Data with Multiple Predictors

Let's look at the solution of the previous exercise.

We'll cover the following

Solution

Solution

The model we’re going to make is straightforward. We’ll use the glm.nb() function from the MASS package. This decision is in part based on the type of data we’re working with. The data is made up of whole counts of things, dead tadpoles in this case, and so it can’t be negative nor partial values. This sort of data just makes sense for a Poisson or negative binomial distribution.

First, let’s make the full model including all the three predictors and all of their two- and three-way interactions:

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Course Introduction

Introduction to R

Thoughts on Proper Data Analysis

Exploratory Data Analysis and Data Summarization

Introduction to Plotting

Basic Statistical Analysis Using R

More Linear Models in R

Advanced Statistical Analysis Using R

Mixed-effects Model

Advanced Data Wrangling and Plotting

Writing Loops and Functions in R

Appendix

Conclusion

Solution: Explore Data with Multiple Predictors

Solution