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Mastering Python Data Visualization

You're reading from   Mastering Python Data Visualization Generate effective results in a variety of visually appealing charts using the plotting packages in Python

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783988327
Length 372 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. A Conceptual Framework for Data Visualization 2. Data Analysis and Visualization FREE CHAPTER 3. Getting Started with the Python IDE 4. Numerical Computing and Interactive Plotting 5. Financial and Statistical Models 6. Statistical and Machine Learning 7. Bioinformatics, Genetics, and Network Models 8. Advanced Visualization A. Go Forth and Explore Visualization Index

Understanding linear regression

A simple scenario would be where one would like to predict whether a student is likely to be accepted into a college undergraduate program (such as Princeton University) based on the data of the GPA score and the SAT score with sample data as follows:

Understanding linear regression

In order to be able to consider the acceptance versus some score that is a combination of the SAT score and the GPA score, just for the purposes of illustrating an example here (note that this does not resemble the actual admissions process), we will attempt to figure out the line of separation. As the SAT scores vary from 2100 to 2390 along the x axis, we can try five values from y=2490 – 2*i*2000. In the following example, we have 2150 instead of 2000. GPA along the y axis has extreme values as 3.3 and 5.0; therefore, we use the incremental values starting with 3.3 using 3.3+0.2i from one extreme and 5.0-0.2i from the other extreme (with a step size of 0.2).

As a first attempt to see how the data visually...

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