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Information TechnologyR ProgrammingStart: TBA Type: Online / In-class; Evening & Weekends Duration (hr): 40 COURSE DESCRIPTION: 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.
COURSE CONTENT:
Introduction to R
R language resources and books
R Studio
R programming overview (data structures and functions)
Startup files
Regression Analytics example
R data structures
Vectors
Matrices
Lists
Data Frames
Factors and Tables
String Manipulations
R Programming Structures and Functions
Control Statements
Loops
Arithmetic and Boolean Operations and Values
Type Conversion
R Functions
Return Values
Locals, Globals, and Arguments
Nested functions
Math Functions and Operations
Math Functions
Functions for Statistical Distributions
Sorting
Linear Algebra Operations on Vectors and Matrices
Simulations
Built-In Random Generators
Input/Output
Console I/O
Files
Web data capture
Connecting to Databases
Object-Oriented Programming Overview
Objects
Classes
Generic Functions
Data Visualization
the plot() Function
Plotting Multiple Curves on the Same Graph
Operations on Axes
The polygon() Function
3-Dimensional Plots
Statistical Methods
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
Prerequisites:
Basics of Statistics
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