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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

Coefficients of correlation and determination

In this section, we will discuss two related notions – coefficients of correlation and coefficients of determination.

Coefficients of correlation

A coefficient of correlation is a measure of the statistical linear relationship between two variables and can be computed using the following formula:

r =  1 _ n 1 Σ i=1 n (x i   x  _ s x )(y i   y  _ s y )

The reader can go here – https://shiny.rit.albany.edu/stat/corrsim/ – to simulate the correlation relationship between two variables.

Figure 6.3 – Simulated bivariate distribution

Figure 6.3 – Simulated bivariate distribution

By observing the scatter plots, we can see the direction and the strength of the linear relationship between the two variables and their outliers. If the direction is positive (r>0), then...

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