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R Programming Tutorial

Home » Data Science » Data Science Tutorials » R Programming Tutorial

Basic

What is R Programming Language?

Careers in R Programming

Install R

List of R Packages

R Tools Technology

R Programming Language

DataSet in R

What is RStudio?

R-studio-Functions

R Packages

Time series in R

R Data Types

R for data science

R Operators

R Data Frame

R Analytics Tool

R Tree Package

Vectors in R

Control statement

If Statement in R

If Else Statement in R

Else if in R

Switch Statement in R

Loops

Loops in R

For Loop in R

Nested For Loop in R

While Loop in R

Next in R

Chart/graphs

Graphs in R

Bar Charts in R

Pie Chart in R

Histogram in R

Line Graph in R

Plot Function in R

Scatterplots in R

R Boxplot labels

Regression in R

Simple Linear Regression in R

Linear Regression in R

Multiple Linear Regression in R

Logistic Regression in R

Poisson Regression in R

OLS Regression in R

P-Value in Regression

Anova in R

ANOVA in R

One Way ANOVA in R

Two Way ANOVA in R

Data Structure

R list

Arrays in R

Data Frames in R

Factors in R

R Vectors

Advanced

Statistical Analysis with R

R String Functions

Data Exploration in R

R CSV Files

KNN Algorithm in R

Sorting in R

lm Function in R

Hierarchical Clustering in R

R Normal Distribution

Binomial Distribution in R

Decision Tree in R

GLM in R

Arima Model in R

Linear Model in R

Predict Function in R

Survival Analysis in R

Standard Deviation in R

Statistical Analysis in R

Predictive Analysis in R

T-test in R

Database in R

Programs

Functions in R

Boxplot in R

R Program Functions

Factorial in R

Random Number Generator in R

Interview question

R Interview Questions

R Programming Tutorial and Resources

It is one of the important Business Analytic tools that can use for each and every organization. It is a programming language and it is a free software environment used for the business analysis with visualization. It was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand. The R software is widely used by data scientists, business analysts, and business intelligence. Major corporations like Facebook and Airbnb use it, and Google is used for analysis. Through the analysis, we can make better solutions for business growth. It comprises the collection of libraries specially designed for analysis. It is very easy to install, and nowadays, we are using R –studio created by John Chambers.

Reasons to Learn R Programming

  • If you need an improvement in your business, usage of R software is very essential to achieve a goal.
  • It performs a wide variety of functions such as data manipulation, data visualization, and statistical modeling.
  • R is a low-level programming language very easy to learn because it makes harder things easy.
  • It provides quality plotting and graphing for data.
  • It is platform-independent, and it is used for machine learning purposes.
  • It has continuous growth.

Applications of R programming Software

It has a wide range of applications in various fields. Here I am introducing some major applications: Finance, Banking, Healthcare, Social media, E-commerce, and manufacturing field.
Finance: Data science that is widely used in the financial industry for the analysis, risk management, and visualization
Banking: It is used for risk analysis, customer quality, customer segmentation, and retention.
Healthcare: It has heavy usage of R. The fields are Genetics, Bioinformatics, Drug Discovery, and Epidemiology
Social Media: It is used to analyze segment potential customers and target them for selling your products.
Manufacturing: Most companies use this software to find customer sentiment and interests.
E-Commerce: It is one of the most important sectors of data science that can be used with R software. Because the e-commerce company deals with the various forms of structured and unstructured data varying from data sources like spreadsheets and databases, it helps analyze the cross-selling products to their customers. We can suggest additional products for the customers. R., For example, can find this type of analysis and recommendations if we own an e-commerce website for your business. In that you can get various forms of data from different sources if you are using R software for the analysis, it helps us find suggestions and recommendations to help us achieve our business goal.

Pre-requisites

As a student, professional, and reader, you should have some basic computer knowledge and programming knowledge. This will help you to learn quickly.

Target Audience

R is very useful, and we can learn quickly, and it is specially designed for analysis, statistical analysis, and visualizations. It can be used by data scientists, business analysts, and business intelligence analysts. Through the analysis, it helps the organization's business growth in various fields it helps to find out future trends in our business.

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