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Building Statistical Models in Python

You're reading from   Building Statistical Models in Python Develop useful models for regression, classification, time series, and survival analysis

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Product type Paperback
Published in Aug 2023
Publisher Packt
ISBN-13 9781804614280
Length 420 pages
Edition 1st Edition
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Authors (3):
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Huy Hoang Nguyen Huy Hoang Nguyen
Author Profile Icon Huy Hoang Nguyen
Huy Hoang Nguyen
Paul N Adams Paul N Adams
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Paul N Adams
Stuart J Miller Stuart J Miller
Author Profile Icon Stuart J Miller
Stuart J Miller
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Toc

Table of Contents (22) Chapters Close

Preface 1. Part 1:Introduction to Statistics
2. Chapter 1: Sampling and Generalization FREE CHAPTER 3. Chapter 2: Distributions of Data 4. Chapter 3: Hypothesis Testing 5. Chapter 4: Parametric Tests 6. Chapter 5: Non-Parametric Tests 7. Part 2:Regression Models
8. Chapter 6: Simple Linear Regression 9. Chapter 7: Multiple Linear Regression 10. Part 3:Classification Models
11. Chapter 8: Discrete Models 12. Chapter 9: Discriminant Analysis 13. Part 4:Time Series Models
14. Chapter 10: Introduction to Time Series 15. Chapter 11: ARIMA Models 16. Chapter 12: Multivariate Time Series 17. Part 5:Survival Analysis
18. Chapter 13: Time-to-Event Variables – An Introduction 19. Chapter 14: Survival Models 20. Index 21. Other Books You May Enjoy

Who this book is for

Professionals in most industries can benefit from the tools in this book. The tools provided are useful primarily at a higher level of inferential analysis, but can be applied to deeper levels depending on the industry in which the practitioner wishes to apply them. The target audiences of this book are:

  • Industry professionals with limited statistical or programming knowledge who would like to learn to use data for testing hypotheses they have in their business domain
  • Data analysts and scientists who wish to broaden their statistical knowledge and find a set of tools and their implementations for performing various data-oriented tasks

The ground-up approach of this book seeks to provide entry into the knowledge base for a wide audience and therefore should neither discourage novice-level practitioners nor exclude advanced-level practitioners from the benefits of the materials presented.

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