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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

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

Packages and settings - R and Python

The core R packages help us with most of the analysis, and we need only the additional package faraway. We first set the path and load the R packages followed by Python essentials:

Set the working directory:
```
setwd("MyPath/R/Chapter_06")
```
Load the required R package:
```
library(aplpack)
```
Complete the Python settings, actually Jupyter notebook (also, refer to Chapter 6, Linear Regression Analysis, ipynb):

The rest of the chapter is locked

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Tech Concepts

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