R is a programming language used to carry out statistical analysis on datasets. This course covers the basics to get started with programming in R. This course demonstrates R using basic statistic functions, data handling, and visual representation through charts, graphs, and plots.

## Learning Objectives

Introduction

- start the course
- install R in Microsoft Windows
- install the RStudio IDE
- navigate the R Console within the RStudio IDE
- use the syntax for if-else, operators, loops, and the apply function in R
- create and manipulate basic data types including numeric and string variables
- use the vector and matrix types in R
- install and use packages from the Comprehensive R Archive Network (CRAN)
- create reusable user-defined functions in R
- use the random number generator in R to generate single random numbers, random samples, and other random variates using the norm and binom functions

Debugging

- use traceback and debug to track down errors in your R code
- use the browser and recover functions to find bugs in R

Data Handling

- read input and format output using the Console in R
- import data from a CSV file in R
- import data from an Excel spreadsheet in R
- handle missing or unknown values in data problems in R
- use the built-in examples to understand R functions

Basic Statistics

- use the mean function in R
- use the median function in R
- use the mode function in R
- use R to measure the spread and dispersion in a dataset
- use R to measure the median absolute deviation
- use R to measure covariance and correlation between two different datasets
- use the R table function to cross tabulate data

Visualizing Data

- use R to create pie charts from datasets
- use R to create bar plots from datasets
- use R to create box plots from datasets
- use R to create histograms from datasets
- use R to create line plots from datasets
- use R to create scatter plots from datasets
- use R to export graphics such as charts and plots for use in other software

Practice: Introduction to R Programming

- understand the basics of the R statistical programming language