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Building Statistical Models in Python

You're reading from  Building Statistical Models in Python

Product type Book
Published in Aug 2023
Publisher Packt
ISBN-13 9781804614280
Pages 420 pages
Edition 1st Edition
Languages
Concepts
Authors (3):
Huy Hoang Nguyen Huy Hoang Nguyen
Profile icon Huy Hoang Nguyen
Paul N Adams Paul N Adams
Profile icon Paul N Adams
Stuart J Miller Stuart J Miller
Profile icon 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 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

Chi-square goodness-of-fit

The chi-square goodness-of-fit test compares the count of occurrences of multiple factor levels for a single variable (factor) to determine whether the levels are statistically equal. For example, a vendor offers three models of phones – three levels (brands) of the single factor (phone) – to customers, who purchase in total an average of 90 phones per week. We can say the expected frequency is 1/3 – so, 30 phones of each model are sold per week, on average. Pearson’s chi-square test statistic, which is calculated by measuring the observed frequencies against expected frequencies, is the test statistic used for the chi-square goodness-of-fit test. The linear equation for this test statistic is as follows:

χ 2 = (O i E i) 2 _ E i , degrees of freedom = k-1

Where O i is the observed frequency, E i, is the expected frequency, and k is the number of factor...

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