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Regression Analysis with R

You're reading from   Regression Analysis with R Design and develop statistical nodes to identify unique relationships within data at scale

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788627306
Length 422 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with Regression FREE CHAPTER 2. Basic Concepts – Simple Linear Regression 3. More Than Just One Predictor – MLR 4. When the Response Falls into Two Categories – Logistic Regression 5. Data Preparation Using R Tools 6. Avoiding Overfitting Problems - Achieving Generalization 7. Going Further with Regression Models 8. Beyond Linearity – When Curving Is Much Better 9. Regression Analysis in Practice 10. Other Books You May Enjoy

Association between variables – covariance and correlation

In the previous chapter, we introduced correlation concepts, and it is now necessary to deepen these concepts. This will help us understand how to use this information in advance and find possible relationships between variables. Let's start with a real example: a company at the launch of a new printer model wants to analyze sales at a number of stores to determine the best price. The following table shows the sales of the product in the last month and the sale price for these stores:

...

Store

SoldItems

Price

Store

SoldItems

Price

Store1

100

60

Store11

145

42

Store2

150

43

Store12

125

47

Store3

130

48

Store13

135

44

Store4

140

45

Store14

105

54

Store5

110

55

Store15

155

39

Store6

160

40

Store16

110

52

Store7

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