Syllabus

Syllabus we covered

Module 1

Introduction to R

Getting Started with R

Introduction to R and RStudio
Installing R and RStudio
Basic R syntax and commands
RStudio interface overview

Basic R Operations

Arithmetic operations
Variables and data types (numeric, character, logical)
Basic functions and help in R

Module 2

Data Structures in R - Part 1

Vectors and Factors

Creating and manipulating vectors
Vector operations
Factors and categorical data

Matrices and Arrays

Creating matrices and arrays
Indexing and subsetting
Matrix operations

Module 3

Data Structures in R - Part 2

Lists

Creating and manipulating lists
List operations

Data Frames

Creating and manipulating data frames
Importing and exporting data (CSV, Excel)

Module 4

Data Manipulation

Data Cleaning and Preparation

Handling missing values
Data transformations
String manipulation

dplyr Package

Introduction to the dplyr package
Select, filter, mutate, arrange, and summarize functions

Module 5

Data Visualization - Part 1

Base R Graphics

Basic plots (histograms, scatter plots, bar plots)
Customizing plots

ggplot2 Package

Introduction to ggplot2
Grammar of graphics
Creating and customizing plots with ggplot2

Module 6

Control Structures

Conditional Statements

if, else if, else statements

Loops

for loops, while loops, repeat loops
Efficient looping techniques

Module 7

Functions

Writing Functions

Function creation and syntax
Scope and environment

Advanced Function Concepts

Anonymous functions
Function debugging and error handling

Module 8

Working with Dates and Times

Date and Time Basics

Date and time classes in R
Formatting and manipulating dates and times

Lubridate Package

Introduction to the lubridate package
Date-time manipulation with lubridate

Module 9

Statistical Analysis

Descriptive Statistics

Measures of central tendency and variability
Summary statistics

Inferential Statistics

Hypothesis testing
t-tests, chi-square tests

Module 10

Advanced Topics and Final Project

Advanced Data Manipulation

Working with large datasets
Data.table package

Final Project Presentation

Students present their final projects
Feedback and discussion
Assessment and Evaluation
Module-based assignments and quizzes
Mid-course project
Final project and presentation