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Hands-On Exploratory Data Analysis with R

You're reading from  Hands-On Exploratory Data Analysis with R

Product type Book
Published in May 2019
Publisher Packt
ISBN-13 9781789804379
Pages 266 pages
Edition 1st Edition
Languages
Authors (2):
Radhika Datar Radhika Datar
Profile icon Radhika Datar
Harish Garg Harish Garg
Profile icon Harish Garg
View More author details

Table of Contents (17) Chapters

Preface 1. Section 1: Setting Up Data Analysis Environment
2. Setting Up Our Data Analysis Environment 3. Importing Diverse Datasets 4. Examining, Cleaning, and Filtering 5. Visualizing Data Graphically with ggplot2 6. Creating Aesthetically Pleasing Reports with knitr and R Markdown 7. Section 2: Univariate, Time Series, and Multivariate Data
8. Univariate and Control Datasets 9. Time Series Datasets 10. Multivariate Datasets 11. Section 3: Multifactor, Optimization, and Regression Data Problems
12. Multi-Factor Datasets 13. Handling Optimization and Regression Data Problems 14. Section 4: Conclusions
15. Next Steps 16. Other Books You May Enjoy

Multi-Factor Datasets

This chapter will introduce a multi-factor dataset and explain how to use exploratory data analysis techniques to analyze this data. In previous chapters, we focused on univariate and multivariate datasets. Univariate and multivariate datasets represent two patterns to statistical analysis. Univariate analysis involves the analysis of a single variable, while multivariate analysis involves the analysis of two or more variables. Most multivariate analysis involves implementation of dependent variable and multiple independent variables. Multiple factor datasets simultaneously analyze several tables of variables to obtain results. In this chapter, we will first learn to read and tidy the data, after which we will learn to map and understand the underlying structure of the dataset and identify the important variables. We will then create a list of outliers or...

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