R Programming

Course Overview:

The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples. An Introduction to R, you will master the basics of this widely used open-source language, including factors, lists, and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis.

Course Content:

Introduction 

♦ What is R?

♦ Why R?

♦ Installing R

♦ R environment

♦ How to get help in R

♦ R Studio Overview

The understanding R data structure

♦ Variables in R

♦ Scalars

♦ Vectors

♦ Matrices

♦ List

♦ Data frames

♦ Cbind, Rbind, attach and detach functions in R

♦ Factors

♦ Getting a subset of Data

♦ Missing values

♦ Converting between vector types

Importing data

♦ Reading Tabular Data files

♦ Reading CSV files

♦ Importing data from excel

♦ Loading and storing data with a clipboard

♦ Accessing database

♦ Saving in R data

♦ Loading R data objects

♦ Writing data to file

♦ Writing text and output from analyses to file

Manipulating Data

♦ Selecting rows/observations

♦ Rounding Number

♦ Creating string from a variable

♦ Search and Replace a String or Number

♦ Selecting columns/fields

♦ Merging data

♦ Relabeling the column names

♦ Data sorting

♦ Data aggregation

♦ Finding and removing duplicate records

Using functions in R

♦ Apply Function Family

♦ Commonly used Mathematical Functions

♦ Commonly used Summary Functions

♦ Commonly used String Functions

♦ User-defined functions

♦ local and global variable

♦ Working with dates

R Programming

♦ While loop

♦ If loop

♦ For loop

♦ Arithmetic operations

Charts and Plots

♦ Box plot

♦ Histogram

♦ Pie graph

♦ Line chart

♦ Scatterplot

♦ Developing graphs

♦ Cover all the current trending packages for Graphs

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