Bayesian statistics the fun way : understanding statistics and probability with Star Wars, LEGO, and Rubber Ducks / Will Kurt.

Format:

Book

Author/Creator:

Kurt, Will, author.

Language:

English

Subjects (All):

Bayesian statistical decision theory.

Probabilities.

Physical Description:

1 online resource

Edition:

1st edition

Place of Publication:

San Francisco, California : No Starch Press, [2019]

System Details:

text file

Summary:

Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that. This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples. By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to: - How to measure your own level of uncertainty in a conclusion or belief - Calculate Bayes theorem and understand what it's useful for - Find the posterior, likelihood, and prior to check the accuracy of your conclusions - Calculate distributions to see the range of your data - Compare hypotheses and draw reliable conclusions from them Next time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

Contents:

Intro

Title Page

Copyright Page

Dedication

About the Author

About the Technical Reviewer

Brief Contents

Contents in Detail

Acknowledgments

Introduction

Why Learn Statistics?

What Is "Bayesian" Statistics?

What's in This Book

Background for Reading the Book

Now Off on Your Adventure!

Part I: Introduction to Probability

1. Bayesian Thinking and Everyday Reasoning

Reasoning About Strange Experiences

Gathering More Evidence and Updating Your Beliefs

Comparing Hypotheses

Data Informs Belief

Belief Should Not Inform Data

Wrapping Up

Exercises

2. Measuring Uncertainty

What Is a Probability?

Calculating Probabilities by Counting Outcomes of Events

Calculating Probabilities as Ratios of Beliefs

3. The Logic of Uncertainty

Combining Probabilities with AND

Combining Probabilities with OR

4. Creating a Binomial Probability Distribution

Structure of a Binomial Distribution

Understanding and Abstracting Out the Details of Our Problem

Counting Our Outcomes with the Binomial Coefficient

Example: Gacha Games

5. The Beta Distribution

A Strange Scenario: Getting the Data

The Beta Distribution

Reverse-Engineering the Gacha Game

Part II: Bayesian Probability and Prior Probabilities

6. Conditional Probability

Introducing Conditional Probability

Conditional Probabilities in Reverse and Bayes' Theorem

Introducing Bayes' Theorem

7. Bayes' Theorem with LEGO

Working Out Conditional Probabilities Visually

Working Through the Math

8. The Prior, Likelihood, and Posterior of Bayes' Theorem

The Three Parts

Investigating the Scene of a Crime.

Considering Alternative Hypotheses

Comparing Our Unnormalized Posteriors

9. Bayesian Priors and Working with Probability Distributions

C-3PO's Asteroid Field Doubts

Determining C-3PO's Beliefs

Accounting for Han's Badassery

Creating Suspense with a Posterior

Part III: Parameter Estimation

10. Introduction to Averaging and Parameter Estimation

Estimating Snowfall

Means for Measurement vs. Means for Summary

11. Measuring the Spread of Our Data

Dropping Coins in a Well

Finding the Mean Absolute Deviation

Finding the Variance

Finding the Standard Deviation

12. The Normal Distribution

Measuring Fuses for Dastardly Deeds

The Normal Distribution

Solving the Fuse Problem

Some Tricks and Intuitions

"N Sigma" Events

The Beta Distribution and the Normal Distribution

13. Tools of Parameter Estimation: The PDF, CDF, and Quantile Function

Estimating the Conversion Rate for an Email Signup List

The Probability Density Function

Introducing the Cumulative Distribution Function

The Quantile Function

14. Parameter Estimation with Prior Probabilities

Predicting Email Conversion Rates

Taking in Wider Context with Priors

Prior as a Means of Quantifying Experience

Is There a Fair Prior to Use When We Know Nothing?

PART IV: Hypothesis Testing: The Heart of Statistics

15. From Parameter Estimation to Hypothesis Testing: Building a Bayesian A/B Test

Setting Up a Bayesian A/B Test

Monte Carlo Simulations

16. Introduction to the Bayes Factor and Posterior Odds: The Competition of Ideas

Revisiting Bayes' Theorem.

Building a Hypothesis Test Using the Ratio of Posteriors

17. Bayesian Reasoning in the Twilight Zone

Bayesian Reasoning in the Twilight Zone

Using the Bayes Factor to Understand the Mystic Seer

Developing Our Own Psychic Powers

18. When Data Doesn't Convince You

A Psychic Friend Rolling Dice

Arguing with Relatives and Conspiracy Theorists

19. From Hypothesis Testing to Parameter Estimation

Is the Carnival Game Really Fair?

Building a Probability Distribution

From the Bayes Factor to Parameter Estimation

A. A Quick Introduction to R

R and RStudio

Creating an R Script

Basic Concepts in R

Functions

Random Sampling

Defining Your Own Functions

Creating Basic Plots

Exercise: Simulating a Stock Price

Summary

B. Enough Calculus to Get By

The Fundamental Theorem of Calculus

C. Answers to the Exercises

Index.

Notes:

Includes bibliographical references and index.

Includes index.

Description based on print version record.

ISBN:

9781098122492

1098122496

9781593279578

1593279574

OCLC:

1108874742