Description

R is a programming language and software environment for statistical analysis, graphics representation and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac. This programming language was named R, based on the first letter of first name of the two R authors (Robert Gentleman and Ross Ihaka), and partly a play on the name of the Bell Labs Language S.

This tutorial is designed for software programmers, statisticians and data miners who are looking forward for developing statistical software using R programming. If you are trying to understand the R programming language as a beginner, this tutorial will give you enough understanding on almost all the concepts of the language from where you can take yourself to higher levels of expertise.

Before proceeding with this tutorial, you should have a basic understanding of Computer Programming terminologies. A basic understanding of any of the programming languages will help you in understanding the R programming concepts and move fast on the learning track.

What you'll learn

Become a UX designer.

You will be able to add UX designer to your CV

Become a UI designer.

Build & test a full website design.

Create your first UX brief & persona.

How to use premade UI kits.

Create quick wireframes.

Downloadable exercise files

Build a UX project from beginning to end.

Learn to design websites & mobile phone apps.

All the techniques used by UX professionals

You will be able to talk correctly with other UX design.

Requirements

  • You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
  • No previous design experience is needed.
  • No previous Adobe XD skills are needed.

Course Content

R Tutorial
R Overview
R Environment Setup
R Basic Syntax
R Data Types
R Variables
R Operators
R Decision making
R Loops
R Functions
R Strings
R Vectors
R Lists
R Matrices
R Arrays
R Factors
R Data Frames
R Packages
R Data Reshaping
R Data Interfaces
R CSV Files
R Binary Files
R XML Files
R JSON Files
R Web Data
R Charts & Graphs
R Pie Charts
R Bar Charts
R Boxplots
R Histograms
R Line Graphs
R Scatterplots
R Statistics Examples
R Linear Regression
R Multiple Regression
R Logistic Regression
R Normal Distribution
R Binomial Distribution
R Poisson Regression
R Analysis of Covariance
R Time Series Analysis
R Nonlinear Least Square
R Decision Tree
R Random Forest
R Survival Analysis
R Interview Questions
R Quick Guide
R Useful Resources

Instructor

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W3edify Infotech

President of Sales

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