# JNTU-K B.TECH R-19 IT 3-1 Syllabus For R programming PDF 2022

### Get Complete Lecture Notes for R programming on Cynohub APP

You will be able to find information about R programming along with its Course Objectives and Course outcomes and also a list of textbook and reference books in this blog.You will get to learn a lot of new stuff and resolve a lot of questions you may have regarding R programming after reading this blog. R programming has 5 units altogether and you will be able to find notes for every unit on the CynoHub app. R programming can be learnt easily as long as you have a well planned study schedule and practice all the previous question papers, which are also available on the CynoHub app.

All of the Topic and subtopics related to R programming are mentioned below in detail. If you are having a hard time understanding R programming or any other Engineering Subject of any semester or year then please watch the video lectures on the official CynoHub app as it has detailed explanations of each and every topic making your engineering experience easy and fun.

### R programming Unit One

#### UNIT 1

Introduction, How to run R, R Sessions and Functions, Basic Math, Variables, Data Types, Vectors, Conclusion, Advanced Data Structures, Data Frames, Lists, Matrices, Arrays, Classes.

### R programming Unit Two

#### UNIT 2

R Programming Structures, Control Statements, Loops, -Looping Over Nonvector Sets,-If-Else, Arithmetic and Boolean Operators and values, Default Values for Argument, Return Values, Deciding Whether to explicitly call return-Returning Complex Objects, Functions are Objective, No Pointers in R, Recursion, A Quicksort Implementation-Extended Extended Example: A Binary Search Tree.

### R programming Unit Three

#### UNIT 3

Doing Math and Simulation in R, Math Function, Extended Example Calculating Probability-Cumulative Sums and Products-Minima and Maxima-Calculus, Functions Fir Statistical Distribution, Sorting, Linear Algebra Operation on Vectors and Matrices, Extended Example: Vector cross Product-Extended Example: Finding Stationary Distribution of Markov Chains, Set Operation, Input /out put, Accessing the Keyboard and Monitor, Reading and writer Files.

### R programming Unit Four

#### UNIT 4

Graphics, Creating Graphs, The Workhorse of R Base Graphics, the plot() Function –Customizing Graphs, Saving Graphs to Files.

### R programming Unit Five

#### UNIT 5

Probability Distributions, Normal Distribution-Binomial Distribution-Poisson Distributions Other Distribution, Basic Statistics, Correlation and Covariance, T-Tests,-ANOVA. Linear Models, Simple Linear Regression, -Multiple Regression Generalized Linear Models, Logistic Regression, -Poisson
Regression-other Generalized Linear Models-Survival Analysis, Nonlinear Models, Splines-Decision-Random Forests.

### R programming Course Objectives

After taking the course, students will be able to Use R for statistical programming, computation, graphics, and modelingWrite functionsand use R in an efficient wayFit some basic types of statistical models Use R in their own researchBe able to expand their knowledge of R on their own

### R programming Course Outcomes

At the end of this course, students will be able to: Demonstrationand implement of basic R programming framework and data structuresExplain critical R programming language concepts such as control structures and recursion Applying mathematical and statistical operations data structures in R Examine data-sets to create testable hypotheses and identify appropriate statistical tests Make use ofappropriate statistical tests using R and Create and edit visualizations with regression models Definemodel choices and results

### R programming Text Books

1)The Art of R Programming, Norman Matloff, Cengage Learning 2)R for Everyone, Lander, Pearson

### R programming Reference Books

1)R Cookbook, PaulTeetor, Oreilly. 2)R in Action,Rob Kabacoff, Manning