R Basics 2. R Basics

2. R Basics

In this book, we will be using the R software environment for all our analysis. You will learn R and data analysis techniques simultaneously. To follow along you will therefore need access to R. We also recommend the use of an integrated development environment (IDE), such as RStudio, to save your work. Note that it is common for a course or workshop to offer access to an R environment and an IDE through your web browser, as done by RStudio cloud. If you have access to such a resource, you don’t need to install R and RStudio. However, if you intend on becoming an advanced data analyst, we highly recommend installing these tools on your computer. Both R and RStudio are free and available online. We suggest to develop your code for the exercises in RStudio and to paste your script in dodona to evaluate them.

		Title	Class progress
		2.1 Case study: US Gun Murders
		2.2 The very basics
		2.3.1. Sum of integers 1,...,100
		2.3.2. Sum of integers 1,...,1000
		2.3.3. Interpret code
		2.3.4. Nested functions
		2.3.5. Interpret code
		2.4 Data types
		2.5.1. Variables in a dataframe
		2.5.2 Variable names
		2.5.3 Examining Variables
		2.5.4 Multiple ways to access variables
		2.5.5 Factors
		2.5.6 Tables
		2.6 Vectors
		2.7 Coercion
		2.8.1-5. Vectors
		2.8.6. Vector of numbers 12..73
		2.8.7. Odd numbers
		2.8.8. Length of a sequence
		2.8.9. Class of seq(1, 10, 0.5)
		2.8.10. Class of seq(1, 10)
		2.8.11. 1 vs 1L
		2.8.12. Vector cast
		2.9 Sorting
		2.10.1-4. Dataframes 1
		2.10.5-6. Dataframes 2
		2.10.7-8. NA
		2.11 Vector arithmetics
		2.12.1. Convert Temperatures
		2.12.2. Vector Sum
		2.12.3. Vector Mean
		2.13 Indexing
		2.14.1-5. Dataframe operations
		2.14.6. Match function
		2.14.7-8. Match operator
		2.15 Basic plots
		2.16.1. Scatter Plot
		2.16.2. Histogram
		2.16.3. Boxplot