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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

Product type Paperback

Published in Aug 2023

Publisher Packt

ISBN-13 9781804614280

Length 420 pages

Edition 1st Edition

Languages

Python

Concepts

Statistics

Authors (3):

Huy Hoang Nguyen

Paul N Adams

Stuart J Miller

View More author details

Table of Contents (22) Chapters

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

Why subscribe?

21. Other Books You May Enjoy

Chi-square test of independence

Suppose we have a dataset of observed vehicle crashes in the state of Texas in 2021, Restraint Use by Injury Severity and Seat Position (https://www.txdot.gov/data-maps/crash-reports-records/motor-vehicle-crash-statistics.html), and want to know whether using a seat belt resulted in a statistically significant difference in fatalities. We have the table of observed values as follows:

	Restrained	Unrestrained	Total
Fatal	1,429	1,235	2,664
Not Fatal	1,216,934	22,663	1,239,597
Total	1,218,363	23,898	1,242,261

Figure 5.6 – Chi-square...

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Authors (3)

Huy Hoang Nguyen

Huy Hoang Nguyen

Huy Hoang Nguyen is a Mathematician and a Data Scientist with far-ranging experience, championing advanced mathematics and strategic leadership, and applied machine learning research. He holds a Master's in Data Science and a PhD in Mathematics. His previous work was related to Partial Differential Equations, Functional Analysis and their applications in Fluid Mechanics. He transitioned from academia to the healthcare industry and has performed different Data Science projects from traditional Machine Learning to Deep Learning.

See other products by Huy Hoang Nguyen

Stuart J Miller

Stuart J Miller

Stuart Miller is a Machine Learning Engineer with degrees in Data Science, Electrical Engineering, and Engineering Physics. Stuart has worked at several Fortune 500 companies, including Texas Instruments and StateFarm, where he built software that utilized statistical and machine learning techniques. Stuart is currently an engineer at Toyota Connected helping to build a more modern cockpit experience for drivers using machine learning.

See other products by Stuart J Miller

Paul N Adams

Paul N Adams

Paul Adams is a Data Scientist with a background primarily in the healthcare industry. Paul applies statistics and machine learning in multiple areas of industry, focusing on projects in process engineering, process improvement, metrics and business rules development, anomaly detection, forecasting, clustering and classification. Paul holds a Master of Science in Data Science from Southern Methodist University.

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