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### Applied Multivariate Analysis with R

###### Step by Step Guide to Perform Multivariate Analysis with R

In today's world, Data is everywhere and it is getting easier to produce it , collect it and perform multiple analysis.

This book is designed as a step by step guide on how to perform multivariate analysis with R. It focuses on PCA (Principal Components Analysis) and LDA (Linear Discriminant Analysis).

The book's main idea is to focus on the step by step implementation. It is not necessary to have an advanced knowledge of R but it is recommended to be familiar with the basics of programming, basics of R, Statistics, Math and some Multivariate Methods.

The chapters in the book cover the following:

• Setting Up the R environment.
• A brief introduction to R.
• Using R for Multivariate Analysis.
• Plotting Multivariate Data.
• Calculating Summary Statistics for Multivariate Data.
• Calculating Correlations for Multivariate Data.
• Standardising Variables.
• Principal Component Analysis.
• Linear Discriminant Analysis.

Check out other books from the author:

Applied Multivariate Analysis with Python

Data Science Workflow for Beginners

DevOPs

Javascript Snippets

Appwrite Up and Running

Front End Developer Interview Questions

ReactJS Documentation

Backend Developer Interview Questions

VueJS Documentation

• ### Categories

• R
• Data Science
• Computers and Programming
• Computer Science
• ### Feedback

Email the Author(s)

A.J. García

I started my coding career back in 2003. Lately I've been involved a lot in Javascript for frontend and the backend.

I would love passing along to you some of the experiences and challenges I've faced over the years.

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• Other Books by Alejandro
• Recommended Resources
• Introduction
• Who is this book for ?
• What this book covers ?
• Setting Up the R environment
• How to check if R is installed on a Windows PC
• Installing R on a Windows PC
• How to install R on non-Windows computers (eg. Macintosh or Linux computers)
• Installing R packages
• How to install an R package
• How to install a Bioconductor R package
• Running R
• A brief introduction to R
• Using R for Multivariate Analysis
• Reading Multivariate Analysis Data into R
• Plotting Multivariate Data
• A Matrix Scatterplot
• A Scatterplot with the Data Points Labelled by their Group
• A Profile Plot
• Calculating Summary Statistics for Multivariate Data
• Means and Variances Per Group
• Between-groups Variance and Within-groups Variance for a Variable
• Between-groups Covariance and Within-groups Covariance for Two Variables
• Calculating Correlations for Multivariate Data
• Standardising Variables
• Principal Component Analysis
• Deciding How Many Principal Components to Retain
• Scatterplots of the Principal Components
• Linear Discriminant Analysis
• Separation Achieved by the Discriminant Functions
• A Stacked Histogram of the LDA Values
• Scatterplots of the Discriminant Functions
• Allocation Rules and Misclassification Rate
• Keep developing your Data Science skills

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