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R for Data Science

You're reading from R for Data Science Learn and explore the fundamentals of data science with R

Product type Paperback

Published in Dec 2014

Publisher

ISBN-13 9781784390860

Length 364 pages

Edition 1st Edition

Languages

R

Concepts

Data Science

Author (1):

Dan Toomey

View More author details

Table of Contents (14) Chapters

Preface

1. Data Mining Patterns FREE CHAPTER

2. Data Mining Sequences

3. Text Mining

4. Data Analysis – Regression Analysis

5. Data Analysis – Correlation

6. Data Analysis – Clustering

7. Data Visualization – R Graphics

8. Data Visualization – Plotting

9. Data Visualization – 3D

10. Machine Learning in Action

11. Predicting Events with Machine Learning

12. Supervised and Unsupervised Learning

Index

Chapter 4. Data Analysis – Regression Analysis

Regression analysis is one of the first tools used when analyzing your dataset. It involves estimating the relationship between variables, and often it will give you an immediate insight into the organization of your data.

In this chapter, we will look at tools available in R for regression analysis:

Simple regression
Multiple regression
Multivariate regression
Robust regression

The rest of the chapter is locked

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Authors (1)

Toomey

Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.

See other products by Toomey

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