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

Bayesian statistics the fun way understanding statistics and probability with Star Wars, LEGO, and Rubber Ducks

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...

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Detalles Bibliográficos
Otros Autores: Kurt, Will, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: San Francisco, California : No Starch Press [2019]
Edición:1st edition
Materias:
Bayesian statistical decision theory.
Probabilities.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630669406719
Tabla de Contenidos:
  • 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
  • Wrapping Up
  • Exercises
  • 3. The Logic of Uncertainty
  • Combining Probabilities with AND
  • Combining Probabilities with OR
  • Wrapping Up
  • Exercises
  • 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
  • Wrapping Up
  • Exercises
  • 5. The Beta Distribution
  • A Strange Scenario: Getting the Data
  • The Beta Distribution
  • Reverse-Engineering the Gacha Game
  • Wrapping Up
  • Exercises
  • Part II: Bayesian Probability and Prior Probabilities
  • 6. Conditional Probability
  • Introducing Conditional Probability
  • Conditional Probabilities in Reverse and Bayes' Theorem
  • Introducing Bayes' Theorem
  • Wrapping Up
  • Exercises
  • 7. Bayes' Theorem with LEGO
  • Working Out Conditional Probabilities Visually
  • Working Through the Math
  • Wrapping Up
  • Exercises
  • 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
  • Wrapping Up
  • Exercises
  • 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
  • Wrapping Up
  • Exercises
  • Part III: Parameter Estimation
  • 10. Introduction to Averaging and Parameter Estimation
  • Estimating Snowfall
  • Means for Measurement vs. Means for Summary
  • Wrapping Up
  • Exercises
  • 11. Measuring the Spread of Our Data
  • Dropping Coins in a Well
  • Finding the Mean Absolute Deviation
  • Finding the Variance
  • Finding the Standard Deviation
  • Wrapping Up
  • Exercises
  • 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
  • Wrapping Up
  • Exercises
  • 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
  • Wrapping Up
  • Exercises
  • 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?
  • Wrapping Up
  • Exercises
  • 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
  • Wrapping Up
  • Exercises
  • 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
  • Wrapping Up
  • Exercises
  • 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
  • Wrapping Up
  • Exercises
  • 18. When Data Doesn't Convince You
  • A Psychic Friend Rolling Dice
  • Arguing with Relatives and Conspiracy Theorists
  • Wrapping Up
  • Exercises
  • 19. From Hypothesis Testing to Parameter Estimation
  • Is the Carnival Game Really Fair?
  • Building a Probability Distribution
  • From the Bayes Factor to Parameter Estimation
  • Wrapping Up
  • Exercises
  • 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
  • Functions
  • The Fundamental Theorem of Calculus
  • C. Answers to the Exercises
  • Index.

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