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.

			Titel	Voortgang groep
			2.1 Case study: US Gun Murders
			2.2 The very basics
			2.3.1. Som van integers 1,...,100
			2.3.2. Som van integers 1,...,1000
			2.3.3. Interpreteer code
			2.3.4. Geneste functies
			2.3.5. Interpreteer code
			2.4 Data types
			2.5.1. Variabelen in een dataframe
			2.5.2 Namen van variabelen
			2.5.3 Variabelen onderzoeken
			2.5.4 Meerdere manieren om toegang te krijgen tot een variabele
			2.5.5 Factors
			2.5.6 Tabellen
			2.6 Vectors
			2.7 Coercion
			2.8.1-5. Vectoren
			2.8.6. Vector van getallen 12..73
			2.8.7. Oneven getallen
			2.8.8. Lengte van een reeks
			2.8.9. Klasse van seq(1, 10, 0.5)
			2.8.10. Klasse van 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