This document outlines an agenda for a session on R programming basics. The session will cover getting started with R Markdown, basic R commands, reading CSV files, exploring and summarizing data through functions like aggregate() and ~ operator, creating cross tabs and chi square tests for categorical variables, visualizing single and categorical variables with histograms and bar plots, converting numeric to categorical variables, renaming factor levels, standardizing/scaling data, and handling missing values. Exercises will accompany sections on data exploration, summarization, cross tabulations, visualization, conversion, renaming levels, standardizing, and handling missing values.

1. Learning a
language is like
building a
muscle
By Prof. Manisha Kapoor
R programming
Basics

2. Agenda :
Session 2 - R
Basics
1. Getting started: R Markdown essentials
2. Basics of working with R Commands
3. How to read csv file
4. Data Exploration
4.1 Data Exploration Functions
4.2 Filtering Data frames & Indexation
Exercise 1 : Data Exploration
4.3 Summarizing Data frames : Aggregate () using ~ operator
Exercise 2 : Data Summarization
5. Creating crosstabs for Categorical variables & chi square test
Exercise 3 : Cross Tabulations
6. Visualization methods of different types of variables
6.1 Create Visualization for single variables : Histograms
6.1 Create Visualization for categorical variables : Bar plots
Exercise 4 : Visualisation
7. Converting numeric variable to categorical variable : Income breaks
Exercise 5 : Conversion Numeric to Categorical
8. Renaming factor levels / categories of categorical variable
Exercise 6 : Renaming Factor Levels
9. Data preparation – Standardizing/Scaling data
Exercise 7 : Standardizing/Scaling data
10. Data preparation – Handling Missing values