R Programming Language

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.

R Language is programmer for statistical analysis. Statistical Analysis plays major role in the Data Analysis. R is support to research and analysis purpose. It is free source software using this we can do machine learning concepts, statistical analysis and deployment to the researcher.

1. Introduction to R

About R, working with tool and explanation

2 Basic Data Types

Data types in R(Numeric , Integer, Complex, Logical, Character) and how to use this Data types in R

3 Objects

Creating Objects(Vectors, Matrices, Factors, Arrays, Data frames),uses and creating objects

4 Functions and Loops Etc.,

Creating, accessing function in R

5 Data Preparation

Data Coding, Data Cleaning, Identification Outlier, Handling Missing Values

6 Statistics

Basics concepts in statistics

7 Regression & Types of Regression

Linear Regression, Multiple Regression , Logistic Regression

8 Classification Methods

Discriminant Analysis – Basics, Rotation Methods involved in DA.

9 Cluster Analysis

Cluster Analysis Basics and real life Examples

10 Analysis of Variance

Anova , Manova

11 Survival Analysis

Types of Non parametric test in Survival and Cox proportional Hazard Rate Model

12 Time series

Forecasting

13 Machine Learning

Algorithms and Coding for Concepts in ML

14 Backup Classes Doubts clarification for all Session

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R Programming Language

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