Instructorstat mat
TypeOnline Course
DateNov 18, 2017
PriceRs.8500
Buy NowBook Now

R Programming

R is a programming language, as well as, a software that offers statistical computing environment and graphics to enable analytical research. It is used by several companies world over today.
Program Objective

This program is designed to offer you a quick insight into the fundamentals of R and slowly help you build that knowledge through systematic learning modules.
Scope of the Training

Starting with an introduction to R, we take you through the verticals of the course, spanning topics related to statistical modelling with R, programming, advanced programming, advanced graphics, R for six sigma professionals and also, R packages.
Who Should Enroll

People who have basic knowledge of operating a computer, statistics and math topics like algebra, vectors and matrices can opt to enrol for this course. It is especially helpful for students interested in statistical analysis, data mining and visualization. Enterprise data analysts and those hoping for a career as R professionals too find this course highly beneficial.
Why Us

At Analytic Square we use simple language, real world data and ample exercises to help you understand the basics of this course. With over 100 lectures and detailed videos that help educate you about R we ensure you get sufficient practice sessions to hone your skills in R.

Section 1Introduction
Lecture 1Installation of R
Lecture 2Getting Started with Libraries
Lecture 3Vector
Lecture 4List
Lecture 5Matrices
Lecture 6Dataframe
Section 2Getting Data in R
Lecture 7Data Types
Lecture 8Subsetting
Lecture 9Writing Data
Lecture 10Reading data from different files
Section 3Functions
Lecture 11Numeric Functions
Lecture 12Charachter Functions
Lecture 13Date Functions
Section 4Subset
Lecture 14Dplyr Package
Lecture 15Control Statement
Section 5Loop
Lecture 16Do Loop
Lecture 17While and Until
Lecture 18Break and Continue
Section 6Reports and Dashboard
Lecture 19Charts, Histograms and Plots
Lecture 20Plotting Functions and Libraries
Section 7Basic Statistics
Lecture 21Measure of Central Tendency
Lecture 22Hypothesis Testing
Lecture 23T-Test
Lecture 24ANOVA
Lecture 25CHI-Square
Lecture 26Correlation
Section 8Statistical Techniques
Lecture 27Linear Regression
Lecture 28Logistic Regression
Lecture 29Cluster Analysis
Lecture 30Time Series
Lecture 31Decision Tree
Lecture 32Random Forest