Data Analysis Using R Software
This course introduces participants to R programming for statistical analysis and research. The goal of this course is to build familiarity with the basic R toolkit for statistical analysis and graphics.
Course Objectives
After completing this course, participants will be able to:

Use R for managing and manipulating data

Explore simple programming in R

Become familiar with some of R's most commonly used statistical procedures

Apply knowledge of the following data mining techniques for complex data sets using R

Multivariate Statistics

Regression

ANOVA

Cluster Analysis

GLM including Logistic Regression

Module 1: Introduction to R

Downloading R and installing packages

Performing basic calculations in R

Vector and matrix arithmetic

Logical selections, using R script files, and reading data into R

How to do loops and if statements to manipulate data
Module 2: Descriptive Statistics in R

Calculating descriptive statistics

Summarizing data (grouped & ungrouped)

Creating tables

Creating graphics
Module 3: Data Mining & Statistical Analysis in R

Hypothesis testing

Regression (Including Stepwise)

ANOVA

Logistic Regression

Chi Square Testing

Cluster Analysis

Decision Trees
Module 4: Case Study – Big Data

Analysis of a large dataset

Reading data into R from CSV files, data manipulation and basic descriptive statistics

Plots and graphing, forloops and ifstatements, and installation of R packages

Identify the purpose of certain lines of code

Practice what has been learned in Modules 13 with a ‘big data’ set

Regression analysis using “big data” set