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You're reading from  Building Statistical Models in Python

Product typeBook
Published inAug 2023
Reading LevelIntermediate
PublisherPackt
ISBN-139781804614280
Edition1st Edition
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Authors (3):
Huy Hoang Nguyen
Huy Hoang Nguyen
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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.
Read more about Huy Hoang Nguyen

Paul N Adams
Paul N Adams
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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.
Read more about Paul N Adams

Stuart J Miller
Stuart J Miller
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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.
Read more about Stuart J Miller

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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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Building Statistical Models in Python
Published in: Aug 2023Publisher: PacktISBN-13: 9781804614280

Authors (3)

author image
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.
Read more about Huy Hoang Nguyen

author image
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.
Read more about Paul N Adams

author image
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.
Read more about Stuart J Miller