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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

Understanding common sampling distributions

A sampling distribution is a probability distribution of a sample statistic based on many samples drawn from a population. In other words, it is the distribution of a particular statistic (such as the mean, median, or proportion) calculated from many sets of samples from the same population, where each set has the same size. There are two things to take note of here. First, the sampling distribution is not about the random samples drawn from the PDF. Instead, it is a distribution that’s made from an aggregate statistic, which comes from another distribution drawn from the PDF. Second, we would need to sample from the PDF in multiple rounds to create the sampling distribution, where each round consists of multiple samples from the PDF.

Let’s look at an exercise in R to illustrate the concept of the sampling distribution using the sample mean as the statistic of interest. We will generate samples from a population whose distribution...

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