This course provides fundamentals of R Programming, very powerful language for statistical computing and graphics. Students will learn how to use R to model data and predict solutions to business problems visualize and optimize data effectively using the built-in tools in R. They will gain fundamental knowledge on Data Analytics and how it assists in data-driven decision making, and master the concepts of statistical analysis like linear & logistic regression, cluster analysis and forecasting. This module also includes basics of Statistics overview.

 

 

Vectors

Matrices

Lists

Data Frames

Factors and Tables

String Manipulations

 

Control Statements

Loops

Arithmetic and Boolean Operations and Values

Type Conversion

R Functions

Return Values

Locals, Globals, and Arguments

Nested functions

 

Math Functions

Functions for Statistical Distributions

Sorting

Linear Algebra Operations on Vectors and Matrices

Simulations

Built-In Random Generators

 

Console I/O

Files

Web data capture

Connecting to Databases

 

Objects

Classes

Generic Functions

 

the plot() Function

Plotting Multiple Curves on the Same Graph

Operations on Axes

The polygon() Function

3-Dimensional Plots

 

Descriptive Statistics

Statistical Distributions

Frequency and contingency tables

Correlation

T test

Non-parametric statistics

Linear Regression

Regression Diagnostics

Robust Regression

Nonlinear regression

Principal Component Analysis

Logistic Regression

Statistical Simulation

 

Basics of Statistics