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The Statistics and Machine Learning with R Workshop

You're reading from   The Statistics and Machine Learning with R Workshop Unlock the power of efficient data science modeling with this hands-on guide

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781803240305
Length 516 pages
Edition 1st Edition
Languages
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Author (1):
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Liu Peng Liu Peng
Author Profile Icon Liu Peng
Liu Peng
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Table of Contents (20) Chapters Close

Preface 1. Part 1:Statistics Essentials
2. Chapter 1: Getting Started with R FREE CHAPTER 3. Chapter 2: Data Processing with dplyr 4. Chapter 3: Intermediate Data Processing 5. Chapter 4: Data Visualization with ggplot2 6. Chapter 5: Exploratory Data Analysis 7. Chapter 6: Effective Reporting with R Markdown 8. Part 2:Fundamentals of Linear Algebra and Calculus in R
9. Chapter 7: Linear Algebra in R 10. Chapter 8: Intermediate Linear Algebra in R 11. Chapter 9: Calculus in R 12. Part 3:Fundamentals of Mathematical Statistics in R
13. Chapter 10: Probability Basics 14. Chapter 11: Statistical Estimation 15. Chapter 12: Linear Regression in R 16. Chapter 13: Logistic Regression in R 17. Chapter 14: Bayesian Statistics 18. Index 19. Other Books You May Enjoy

More on log odds and odds ratio

Recall that the odds refer to the ratio of the probability of an event happening over its complement:

odds =  probability of event happening   ________________________   probability of event not happening  =  p _ 1 p  =  P(y = 1) _ P(y = 0) 

Here, the probability is calculated as follows:

p = P(y = 1) =  1 _ 1 + e z 

1 p = 1  1 _ 1 + e z  =  e z _ 1 + e z 

Plugging in the definition of p and 1 p gives us the following:

odds =  p _ 1 p  = e z

Instead of directly working with the odds, we often use the log odds or logit. This term is typically modeled as a linear combination of predictors in a logistic regression model via the following:

log P(y = 1) _ P(y...

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