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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
Author Profile Icon Paul N Adams
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

The Rank-Sum test

When the assumptions of the t-test are not met, the Rank-Sum test is often a good non-parametric alternative test. While the t-test can be used to test for the difference between the means of two distributions, the Rank-Sum test is used to test for the difference between the locations of two distributions. This difference in the test utility is due to the lack of parametric assumptions in the Rank-Sum test. The null hypothesis of the Rank-Sum test is that the distribution underlying the first sample is the same as the second sample. If the sample distributions appear to be similar, this allows us to use the Rank-Sum test to test for the difference in the locations of the two samples. As stated, the Rank-Sum test cannot specifically be used for testing the difference between means because it does not require assumptions about the sample distributions.

The test statistic procedure

The test procedure is straightforward. The process is outlined here and an example...

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