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Statistical Application Development with R and Python

You're reading from Statistical Application Development with R and Python Develop applications using data processing, statistical models, and CART

Product type Paperback

Published in Aug 2017

Publisher

ISBN-13 9781788621199

Length 432 pages

Edition 2nd Edition

Languages

Python

Concepts

Application Development

Author (1):

Prabhanjan Narayanachar Tattar

View More author details

Table of Contents (12) Chapters

Preface

1. Data Characteristics FREE CHAPTER

2. Import/Export Data

3. Data Visualization

4. Exploratory Analysis

5. Statistical Inference

6. Linear Regression Analysis

7. Logistic Regression Model

8. Regression Models with Regularization

9. Classification and Regression Trees

10. CART and Beyond

Index

Chapter 3. Data Visualization

Data is possibly best understood, wherever plausible, if it is displayed in a reasonable manner. Chen et. al. (2008) have compiled articles where many scientists of data visualization give a deeper, historical and modern trend of data display. Data visualization may be as historical as data itself. It emerges across all the dimensions of science, history, and every stream of life where data is captured. The reader may especially go through the rich history of data visualization in the article of Friendly (2008) from Chen et. al. (2008). The aesthetics of visualization have been described elegantly in Tufte (2001). The current chapter will have a deep impact on the rest of the book, and this chapter aims to provide the guidance and specialized graphics in the appropriate context in the rest of the book.

This chapter provides the necessary stimulus for understanding the gist that discrete and continuous data need appropriate tools, and that validation...

The rest of the chapter is locked

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