R PROGRAMMING LAB

Learning Outcome (at course level)

Learning and teaching strategies

Assessment Strategies

1. Understand and apply various programming concepts in R language
2. Implement various functions using R
3. Analyze the problem and find right solution
4. Implement packages to design and program testing.
5. Understand data and file management using R.
6. Develop and analyze applications using R.

Approach in teaching:

Interactive Lab Sessions,

Modeling, Discussions, implementing enquiry based learning, student centered approach

Learning activities for the students:

Experiential Learning, Discussions, Lab Assignments, Learning through Real life data centric problems

• Lab Assignments
• Practical Record
• Continues Assessment
• Semester End Examination

Contents

Fundamentals

• About R tutorial
• Introduction to R
• About R, Do & Don't
• Why R programming Language

Overview

• General Properties
• First Program - Hello World
• Core Characteristics

Data Types

• Data types introduction
• Data types Examples
• Variable in R Language
• Introduction to Variable

Operators

• Operator Introduction
• Arithmetic Operators
• Relational Operators
• Logical Operators
• Assignment Operators
• Miscellaneous Operators

Decision Making

• Decision Making Introduction
• if statement
• if...else statement
• switch statement
• if…else Ladder
• ifelse() function

Loop control

• Loop Introduction
• for loop
• while Loop
• repeat Loop
• Break Statement
• Next Statement

Array

• Array Introduction

• String
• String Introduction

Function

• Function Introduction
• Your First Function
• Built-in Function

Vector

• Vector Introduction

• Lists
• List Introduction

Matrices

• Matrix Introduction
• Matrix Construction
• Addition & Subtraction
• Multiplication & Division

Factors

• Factor Introduction

Data Frames

• Data Frame Introduction
• Data Frame details
• Filtering and subsetting data
• Aggregate function

Packages

• Package Introduction

Data Reshaping

Data Reshaping Introduction

Data and File Management

• Types of Input
• CSV Files
• Excel file
• Reading and writing data

Charts & Graphs

• Graphical Procedures Introduction
• plot function
• Plot using base graphics
• Plot using ggplot2

Data Analytics

Design and write efficient programs using R to perform routine and specialized data manipulation and analysis tasks using

• Packages
• Data Reshaping
• Charts & Graphs