An interactive introduction to data analysis with R
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In this course, you'll learn the basics of using R for data analysis. This should provide you with the necessary skills to use R when learning more advanced and specialised topics. You don't need any prior experience with R, statistics, or programming to work through this material, however if you already have some experience you can start from any chapter you'd like to learn from.
In R Programming Basics, you will master the basic operations of this popular open source language. You will also learn to perform simple algebraic operations on vectors and matrices. You will also learn about data frames, conditional statements, loops, and functions to power your R code, making your work more efficient and elegant.
With coding comes bugs and errors that need troubleshooting. In this chapter, you will learn how to decipher errors, find help for fixing them, and practice asking clear questions with minimally reproducible examples.
This chapter will teach you the basic project structure and good practice of project management in R. You will also learn how to import data from different sources including csv files, excel files and files hosted online.
This chapter demonstrates how to fit linear models in R. You'll learn about how to fitting simple linear regression, models with categorical variables and interaction effects, and visualising models with ggplot2.