R Training Chennai Statistical

Module 1

Introduction to Statistics

Five Number Summary

The Centre of the Data and the Effects of Extreme Values

The Spread of the Data

The Shape of the Data

Categorical Variables

Some Features of Data

Relationships Between Quantitative and Categorical Variables

Examining Relationships Between Two Categorical Variables

Relationships Between Two Quantitative Variables

Module 2

Data Collection

Sampling

Data Collection

Observational Studies

Data Collection

Experiments

The Need for Probability

Some Probability Basics

Probability Distributions

Long Run Averages

Sampling Distributions

Module 3

Introduction to Confidence Intervals

Confidence Intervals for Proportions

Sample Size for Estimating a Proportion

Confidence Intervals for Means

Robustness of Confidence Intervals

Introduction to Statistical Tests

The Structure of Statistical Tests

Hypothesis Testing for Proportions

Hypothesis Testing for Means

Power and Type I and Type II Errors

Connection Between Confidence Intervals and Hypothesis Testing

Matched Pairs

Module 4

Comparing Two Proportions

Comparing Two Means

The Linear Regression Formula

Regression Coefficients Residuals and Variances

Regression Inference and Limitations

Residual Analysis and Transformations

Module 5

Overview

History of R

Advantages and disadvantages

Downloading and installing

How to find documentation

Module 6

Introduction

Using the R console

Getting help

Learning about the environment

Writing and executing scripts

Saving your work

Module 7

Data Structures and Variables

Variables and assignment

Data types-Indexing, subsetting

Viewing data and summaries

Functions

Naming conventions

Objects,Models,raphics

Module 8

Control Flow

Truth testing

Branching

Looping Vectorized calculations

Module 9

Functions

Parameters

Return values

Variable scope

Exception Handling

Module 10

Getting Data into the R environment

Builtin data

Reading local data

Web data

Module 11

Overview of Statistics in R

Introduction to R Graphics

Model notation

Module 12

Descriptive statistics

Continuous data

Scatter plot,Box plot

Categorical data

Mosaic plot

Correlation

Module 13

Inferential Statistics

T-test and non-parametric

Equivalents-Chi-squared Test

Logistic Regression,

Distribution testing

Power testing

Module 14

Linear Regression

Linear models

Regression plots

ANOVA

Module 15

Other Topics

Classification

Clustering

Time series

Dimensionality reduction

Machine Learning

Module 16

Object Oriented R

Generic functions

S3/S4 classes

Module 17

Installing Packages

Finding resources

Installing resources

Module 18

More about Graphics

Labels

Exporting graphics

Module 19

Sophisticated Graphics in R

Lattice

GGplot2

Interactive graphics

Animated GIF

rGGobi

Module 20

R for Mapping and GIS

Choropleth maps

Layers

Back