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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 1. Data Characteristics

Data consists of observations across different types of variables, and it is vital that any data analyst understands these intricacies at the earliest stage of exposure to statistical analysis. This chapter recognizes the importance of data and begins with a template of a dummy questionnaire and then proceeds with the nitty-gritties of the subject. We will then explain how uncertainty creeps in to the domain of computer science. The chapter closes with coverage of important families of discrete and continuous random variables.

We will cover the following topics:

Identification of the main variable types as nominal, categorical, and continuous variables
The uncertainty arising in many real experiments
R installation and packages
The mathematical form of discrete and continuous random variables and their applications

You have been reading a chapter from

Statistical Application Development with R and Python - Second Edition

Published in: Aug 2017

Publisher:

ISBN-13: 9781788621199

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