JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

22BBA603: R PROGRAMMING

BBA (Data Analytics) VI Semester (R22)

Course Objectives

Learn R programming language, basic functions and techniques.

To introduce to R programming
To understand the usage of expressions and loop in R
To understand list, functions, strings and factors in R
To understand the usage of objects and strings in R
To visualize and analyze the data using R programming Course outcomes: Student will be able to
Get familiarize with R environment
Work with expressions and loops in R
To apply with list, functions, strings and factors in R
To apply on Statistics with R
Visualize and analyze data in using R

UNIT - I: Getting Started with R

Concept of R, installing R, IDE of R, getting help from R, Mathematical Operators and Vectors, Assigning Variables, Special Numbers, classes, different types of numbers, changing classes, examining variables, the workplace, library of package, getting to know a package.

UNIT - II: Basic Expressions

Vectors – sequences, lengths, names, indexing vectors, vector recycling and repetition, Matrices and Arrays – creating arrays and matrices, rows, columns, dimensions, indexing arrays, Arithmetic, Conditional – if and else, vectorized if, multiple selection, Loops – repeat loops, while loops, for loops, Advanced looping – replication, looping over lists, looping over arrays, Multiple – input apply, instant vectorization.

UNIT - III: Lists, Functions, Strings and Factors

Lists – creating lists, automatic and recursive variables, list dimensions and arithmetic, indexing lists, conversion between vectors and lists, Combining lists, NULL, Pairlists, Data Frames – Creating Data Frames, Indexing Data Frames, Basic Data Frame Manipulation, Functions – Creating and Calling Functions, Passing functions, variable scope, Strings – Constructing and printing strings, Formatting numbers, Special characters, Changing case, Extracting Substrings, Splitting Strings, File paths, Factors – Creating, factor levels, ordered factors, conversion of variables .

UNIT - IV: Statistics with R

Summarizing data, calculating relative frequencies, tabulating factors and creating contingency tables, testing categorical variables for independence, calculating quantiles of a dataset, converting data into z-scores, t-test, testing sample proportions, testing normality, comparing means of two samples, testing correlation for significance, linear regression in R, logistic regression in R, clustering with R .

UNIT - V: Packages and Visualization

Loading packages, search path, libraries and installed packages, installing packages, maintaining packages, reading and writing data, importing data using built-in functions, Visualization – The three plotting systems, Scatterplots – based graphics, lattice graphics, histograms, box plots, bar charts, fitting linear model and regression tree.