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Advanced Analytics with R and Tableau

You're reading from   Advanced Analytics with R and Tableau Advanced analytics using data classification, unsupervised learning and data visualization

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781786460110
Length 178 pages
Edition 1st Edition
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Authors (3):
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Roberto Rösler Roberto Rösler
Author Profile Icon Roberto Rösler
Roberto Rösler
Ruben Oliva Ramos Ruben Oliva Ramos
Author Profile Icon Ruben Oliva Ramos
Ruben Oliva Ramos
Jen Stirrup Jen Stirrup
Author Profile Icon Jen Stirrup
Jen Stirrup
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Table of Contents (10) Chapters Close

Preface 1. Advanced Analytics with R and Tableau FREE CHAPTER 2. The Power of R 3. A Methodology for Advanced Analytics Using Tableau and R 4. Prediction with R and Tableau Using Regression 5. Classifying Data with Tableau 6. Advanced Analytics Using Clustering 7. Advanced Analytics with Unsupervised Learning 8. Interpreting Your Results for Your Audience Index

Getting started with multiple regression?


Simple linear regression will summarize the relationship between an outcome and a single explanatory element. However, in real life, things are not always so simple! We are going to use the adult dataset from UCI, which focuses on census data with a view to identifying if adults earn above or below fifty thousand dollars a year. The idea is that we can build a model from observations of adult behavior, to see if the individuals earn above or below fifty thousand dollars a year.

Multiple regression builds a model of the data, which is used to make predictions. Multiple regression is a scoring model, which makes a summary. It predicts a value between 0 and 1, which means that it is good for predicting probabilities.

It's possible to imagine multiple regression as modeling the behavior of a coin being tossed in the air. How will the coin land—heads or tails? It is not dependent on just one thing. The reality is that the result will depend on other variables...

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