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Building Statistical Models in Python
Building Statistical Models in Python

Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis

By Huy Hoang Nguyen , Paul N Adams , Stuart J Miller
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Book Aug 2023 420 pages 1st Edition
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eBook
$39.99 $27.98
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Product Details


Publication date : Aug 31, 2023
Length 420 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781804614280
Category :
Concepts :
Table of content icon View table of contents Preview book icon Preview Book

Building Statistical Models in Python

Part 1:Introduction to Statistics

This part will cover the statistical concepts that are foundational to statistical modeling.

It includes the following chapters:

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Key benefits

  • Gain expertise in identifying and modeling patterns that generate success
  • Explore the concepts with Python using important libraries such as stats models
  • Learn how to build models on real-world data sets and find solutions to practical challenges

Description

The ability to proficiently perform statistical modeling is a fundamental skill for data scientists and essential for businesses reliant on data insights. Building Statistical Models with Python is a comprehensive guide that will empower you to leverage mathematical and statistical principles in data assessment, understanding, and inference generation. This book not only equips you with skills to navigate the complexities of statistical modeling, but also provides practical guidance for immediate implementation through illustrative examples. Through emphasis on application and code examples, you’ll understand the concepts while gaining hands-on experience. With the help of Python and its essential libraries, you’ll explore key statistical models, including hypothesis testing, regression, time series analysis, classification, and more. By the end of this book, you’ll gain fluency in statistical modeling while harnessing the full potential of Python's rich ecosystem for data analysis.

What you will learn

Explore the use of statistics to make decisions under uncertainty Answer questions about data using hypothesis tests Understand the difference between regression and classification models Build models with stats models in Python Analyze time series data and provide forecasts Discover Survival Analysis and the problems it can solve

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Product Details


Publication date : Aug 31, 2023
Length 420 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781804614280
Category :
Concepts :

Table of Contents

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

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