R Crash Course - Learn R-programming in 2 hours: R & RStudio

Install R and RStudio on Windows, download and run the R installer, install RStudio, explore manuals and FAQ, and join the community mailing list for help.

Explore the RStudio layout, including the source, console, environment, and file panes, and learn to set working directories, run code, access help, and use shortcuts for efficient R programming.

Explore the RStudio interface, set up a working directory, and access help and documentation. Learn executing code, running scripts, and viewing plots in an interactive workflow.

Learn about contributed packages in R and how to manage them with CRAN, install and load packages, and call specific functions using the double colon operator.

Learn to install and manage R packages in RStudio, load from repositories or archives, and call specific functions with library, while adding helpful code comments.

Explore calculations in R, using the console or script, with arithmetic operators (+, -, *, /), boolean logic, and variable assignment, then apply modeling formulas and generate sequences.

Perform basic calculations in R and RStudio by typing expressions in the console and viewing outputs. Explore operators, logical operators, and built-in functions like triad and geometry for modeling possibilities.

Explore creating and using variables in R with the assign operator, view results in the environment pane, and perform arithmetic while following the convention of including points in variable names.

Assign variables in R, computing sums like eight plus seven and products like four times two, then print results in the console. Use meaningful names and the environment pane.

Explore data types and data structures in R, including objects and vectors, atomic types (numeric, character, integer, logical, complex), and attributes for efficient, structured coding.

Explore how to assign and convert R variable types, including numeric, integer, character, and logical values, and learn how factors and their levels control data ordering.

Explore vectors as the simplest R data type, containing elements of one class such as character, integer, or numeric. Convert between vectors, matrices, lists, and data frames and use attributes.

Index vectors in R using square brackets, retrieve elements, counting starts at one, exclude entries with negative indices, perform elementwise operations like multiplying by five, and add vectors with recycling.

Learn how to declare and manipulate vectors in R, including six vector types, perform arithmetic, index elements, understand recycling of mismatched lengths, and use built-in functions like max and var.

Explore factors as categorical data in R, learn how strings convert to factors by default, and master integer-based levels in alphabetical order, and the levels argument in RStudio.

Learn to import data into R from csv, excel, and text files by setting the working directory, using read functions with header and separator arguments, and previewing data in RStudio.

Explore matrices as two-dimensional data structures in R, created by matrix or cbind. Index with square brackets and apply scalar, element-wise operations, plus mean and transpose.

Explore how lists in R act as containers for data, created and named with names function, accessed by single or double brackets, and updated by adding or deleting elements.

Learn data frames in R as the primary two-dimensional data type for tabular data, with columns as variables and observations as rows, revealed by structure and summary.

Master indexing and querying data frames in R by using single and double brackets, dollar signs, and boolean conditions to retrieve rows and columns efficiently.

Explore modifying dataframes in R by deleting columns (by index or name), removing rows (by index or condition), and adding columns or new rows using subset and bind operations.

Learn how to handle missing values in R by using is.na, creating logical vectors, and indexing data frames to exclude NA values and compute accurate means.

Explore how functions in R perform tasks, accept arguments, return values, and how to use built-in and user-defined functions with named or positional arguments and default values.

Explore built-in and user-defined R functions, including sqrt and log, and learn to declare a two-argument function for normalized difference with test values.

Explore R control structures, including if, if else, else, while, switch, repeat, break, and return, with simple queries, vectorized forms, and print outputs.

Develop an understanding of for loops in R by iterating over numeric ranges or vector elements, printing results, and using length to determine iterations.

Explore how to use for loops in R to iterate over vectors, print elements, and index results, using length-based iterations or element-based loops for flexible scripting.