Introduction to Writing Functions in R

Writing your own functions makes analyses more readable, reduces errors, and increases reusability across projects. It is considered the single biggest productivity boost for R programmers.

You will work with data on Wyoming tourism, stock price-to-earnings ratios, and grain yields to practice writing practical data science functions in realistic contexts.

Yes. Chapter 3 covers how R decides which variables exist and are accessible, including return values, early returns, and returning multiple values from a function.

You should have completed Introduction to R, Intermediate R, and Introduction to the Tidyverse. Comfort with vectors, data frames, and dplyr pipelines is expected.

Yes. The final chapter is a case study on grain yields where you apply your function writing skills to data preparation, visualization, and modeling tasks.