# R AND DATA ANALYTICS

R is an open source programming language and software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R's popularity has increased substantially in recent years.

## INTRODUCTION TO R

• What is R
• History of R
• Features of R
• SAS versus R
• S and S-plus
• Obtaining and managing R
• Installing R
• Packages
• R interfaces
• R Library

## R objects and Data types

• Vector
• Matrix
• Array
• Factor
• List
• Data Frame
• Factors
• NA/NAN
• Explicit Coercion
• Lists
• Missing Value

## Inbuilt Functions of R>

• Environment functions
• Statistical Functions
• Text Functions
• Mathematical Functions
• Reading Data from R
• Writing Data into R
• Files connection

• If
• For
• Repeat
• While
• Next
• Return

• Lappy
• Tappy
• Split
• Mappy
• Apply

## Date and time in R

• Dates in R
• Time in R
• Operation on Dates and Time on R

## Basic Graphs in R

• Creating a graph
• Density Plot
• Dot Plot
• Bar Plot
• Line Charts
• Pie Charts
• Box Plot
• Scatter Plot
• Histogram
• Normal QQ Plot

## Advance Graphs in R

• Graphical Parameters
• Lattice Graphs
• Combining Plot
• Ggplots Graph
• Probability Graphs
• Correlograms
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## Statistics

• Measure of central Tendency
• Measure of Variances
• Probability distributions

## Predictive Modeling

• Simple Linear Regression
• Multiple Regression
• Logistic Regression
• Poisson Regression

## Classification Methods

• Decision Tree Classifiers
• Bayesian Classifiers
• K-N-N Classifiers
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## Clustering techniques

• K Means
• PAM
• Hierarchical Clustering

## Black Box Methods

• Artificial Neural Network
• Support Vector Machines

## Time Series Analysis

• Autoregressive moving Average
• VAR
• GARCH