This book covers an extensive range of topics in R. It will comfortably and rapidly familiarize you with the basics, before you proceed into in-depth analyses and custom graphics. A brief description of each chapter's content is provided.
In this chapter, we will step through the R installation process. Afterwards, you will launch R and execute your first commands in the R console.
By the end of the chapter, you will be able to:
- Download R
- Install R
- Run R on your computer
- Issue an R command
- Set your R working directory
In this chapter, we will explore the anatomy of the R console in greater depth by solving a challenging puzzle that was presented to us by the late Zhuge Liang.
By the end of the chapter, you will be able to:
- Use proper syntax within the R console
- Comment your R code
- Make calculations using formulas
- Distinguish between different types of input and output in the R console
In this chapter, we will focus on getting our data into R and then manipulating it via variables. We will also learn how to manage the R workspace.
By the end of the chapter, you will be able to:
- Import external data into R
- Use variables to organize and manipulate your data
- Manage the R workspace
In this chapter, we will extensively examine and evaluate our data. This will entail the use of diverse functions to create predictive data models. Throughout this process, we will also consider the practical and statistical meaning behind our analyses.
By the end of the chapter, you will be able to:
- Use multi-argument and variable-argument functions to make calculations
- Create predictive data models using regression analysis
- Consider the statistical and practical significance of your analyses
In this chapter, we will turn towards using our data models to predict outcomes. We will also assess the viability of these outcomes. Along the way, we will create and employ our own custom functions that expand the capabilities of R.
By the end of the chapter, you will be able to:
- Use regression models to predict outcomes
- Create your own custom functions to address specific needs
- Assess the viability of achieving the outcomes predicted by regression models.
In this chapter, our task will be to review and organize a complete data analysis. We will emphasize the need to clarify and communicate our data analyses effectively, which can be achieved through a series of common steps.
By the end of the chapter, you will be able to:
- Organize and clarify your raw R data analyses
- Communicate your raw R data analyses in the most effective manner
- Apply the steps common to all well-conducted R analyses
In this chapter, we will take our first look at R's graphical capabilities by generating several charts, graphs, and plots. Throughout, we will use common graphical parameters to customize these visuals. We will also save and export our graphics for external use.
By the end of the chapter, you will be able to:
- Create six different charts, graphs, and plots in R
- Customize your R visuals using text, colors, axes, and legends
- Save and export your graphics for use outside of R
In this chapter, we will take a deeper look at R's graphical capabilities. We will practice customizing different types of charts, graphs, and plots by modifying their unique parameters. We will also learn how to build our own custom graphics from scratch using R's graphics functions.
By the end of the chapter, you will be able to:
- Customize several charts, graphs, and plots using arguments specific to each
- Use graphics functions to add information to any visual
- Create custom graphics by building them from the ground up
In the final chapter, we will look to the future. We will focus on the ways in which you can learn beyond the contents of this book to further expand your knowledge of R.
By the end of the chapter, you will be able to:
- Use R's built-in help system
- Install packages that expand R's functionality
- Take advantage of electronic learning resources, such as websites, blogs, and online communities