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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 belt, 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. Download Resources [DOWNLOAD RESOURCES: Click here to download the solutions to the book's exercises.](https://nostarch.com/download/Bayes_exercise_solutions_11272023.pdf) Author Bio **Will Kurt** works as a data scientist at Wayfair, and has been using Bayesian statistics to solve real business problems for over half a decade. He frequently blogs about probability on his website, [CountBayesie.com](https://www.countbayesie.com/). Kurt is the author of *Get Programming with Haskell* (Manning Publications) and lives in Boston, Massachusetts. Table of contents Introduction **Part 1: Introduction to Probability** **Chapter 1**: What Do You Believe and How Do You Change it? **Chapter 2**: Measuring Uncertainty **Chapter 3**: The Logic of Uncertainty **Chapter 4**: Probability Distributions 1 **Chapter 5**: Probability Distributions 2 **Part 2: Bayesian Probability and Prior Probabilities** **Chapter 6**: Conditional Probability [**Chapter 7:** Bayes' Theorem with LEGO](https://nostarch.com/download/samples/BayesianStatisticsTheFunWay_Ch07_Sample.pdf) **Chapter 8**: Posterior, Likelihood, and Prior **Chapter 9**: Working with Prior Probability Distributions **Part 3: Parameter Estimation** **Chapter 10**: Intro to Parameter Estimation **Chapter 11**: Measuring the Spread of Data **Chapter 12**: Normal Distribution and Confidence **Chapter 13**: Tools of Parameter Estimation **Chapter 14**: Parameter Estimation with Priors **Part 4: Hypothesis Testing: The Heart of Statistics** **Chapter 15**: From Parameter Estimation to Hypothesis Testing **Chapter 16**: Comparing Hypotheses with Bayes Factor **Chapter 17**: Bayesian Reasoning in the Twilight Zone **Chapter 18**: When Data Doesn't Convince You **Chapter 19**: From Hypothesis Testing to Parameter Estimation Appendix A: A Crash Course in R Appendix B: Enough Calculus to Get By [View the detailed Table of Contents](https://nostarch.com/download/samples/BayesianStatisticsTheFunWay_ToC_Sample.pdf) [View the Index](https://nostarch.com/download/samples/BayesianStatisticsTheFunWay_Index_Sample.pdf) Reviews "An excellent introduction to subjects critical to all data scientists." —**Inside Big Data** "The author uses great examples to clarify key concepts . . . I would highly recommend as a supplement for any stats student or professional looking to refresh on Bayesian statistics." **—Stan T., Design Collective** “The book is an excellent introduction, especially for those of us that have a rough time with advanced math but that want to advance in the data science field.” **—NotAMonadTutorial.com** “The writing is no-nonsense, the content is understandable, the examples are engaging, and the Bayesian concepts are explained clearly . . . As a first introduction to Bayesian inference, this book is hard to beat. It nails the key concepts in a compelling and instructive fashion.” **—BayesianSpectacles.org** “A simple yet complete practical introduction to Bayesian inference and statistics.” **—Jose D. Perezgonzalez, Frontiers in Psychology** Extra Stuff Author interview in **[This is not a Monad tutorial](https://notamonadtutorial.com/interview-with-will-kurt-on-his-latest-book-bayesian-statistics-the-fun-way-63ce8aee32ed)**. Featured in **[Great Lakes Geek](http://www.greatlakesgeek.com/other/books/bayesian-statistics.htm)**. Updates View the [**latest errata**](https://nostarch.com/download/errata/BayesianStatistics_errata_p9.pdf). ## User login - [Log in](https://nostarch.com/user) - [Create account](https://nostarch.com/user/register) ## You might also like... 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[](https://nostarch.com/sites/default/files/styles/uc_product_full/public/Bayesian%20Statistics%20the%20Fun%20Way.jpg?itok=gU9U2hp3 "Bayesian Statistics the Fun Way") Understanding Statistics and Probability with Star Wars, LEGO, and Rubber Ducks by Will Kurt July 2019, 256 pp. ISBN-13: 9781593279561 - [Contents](https://nostarch.com/learnbayes#content) - [Reviews](https://nostarch.com/learnbayes#reviews) - [Updates](https://nostarch.com/learnbayes#updates) **Look Inside\!** [](https://nostarch.com/images/BayesianStatisticsTheFunWay_back.jpg)[](https://nostarch.com/images/BayesianStatisticsTheFunWay_pg_21.jpg)[](https://nostarch.com/images/BayesianStatisticsTheFunWay_pgs_22-23.jpg)[](https://nostarch.com/images/BayesianStatisticsTheFunWay_pg_33.jpg)[](https://nostarch.com/images/BayesianStatisticsTheFunWay_pgs_40-41.jpg) [Download Chapter 7: Bayes' Theorem with LEGO](https://nostarch.com/download/samples/BayesianStatisticsTheFunWay_Ch07_Sample.pdf) **Get the most from your data, and have fun doing it** 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 belt, 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. Download Resources [DOWNLOAD RESOURCES: Click here to download the solutions to the book's exercises.](https://nostarch.com/download/Bayes_exercise_solutions_11272023.pdf) Author Bio **Will Kurt** works as a data scientist at Wayfair, and has been using Bayesian statistics to solve real business problems for over half a decade. He frequently blogs about probability on his website, [CountBayesie.com](https://www.countbayesie.com/). Kurt is the author of *Get Programming with Haskell* (Manning Publications) and lives in Boston, Massachusetts. Table of contents Introduction **Part 1: Introduction to Probability** **Chapter 1**: What Do You Believe and How Do You Change it? **Chapter 2**: Measuring Uncertainty **Chapter 3**: The Logic of Uncertainty **Chapter 4**: Probability Distributions 1 **Chapter 5**: Probability Distributions 2 **Part 2: Bayesian Probability and Prior Probabilities** **Chapter 6**: Conditional Probability [**Chapter 7:** Bayes' Theorem with LEGO](https://nostarch.com/download/samples/BayesianStatisticsTheFunWay_Ch07_Sample.pdf) **Chapter 8**: Posterior, Likelihood, and Prior **Chapter 9**: Working with Prior Probability Distributions **Part 3: Parameter Estimation** **Chapter 10**: Intro to Parameter Estimation **Chapter 11**: Measuring the Spread of Data **Chapter 12**: Normal Distribution and Confidence **Chapter 13**: Tools of Parameter Estimation **Chapter 14**: Parameter Estimation with Priors **Part 4: Hypothesis Testing: The Heart of Statistics** **Chapter 15**: From Parameter Estimation to Hypothesis Testing **Chapter 16**: Comparing Hypotheses with Bayes Factor **Chapter 17**: Bayesian Reasoning in the Twilight Zone **Chapter 18**: When Data Doesn't Convince You **Chapter 19**: From Hypothesis Testing to Parameter Estimation Appendix A: A Crash Course in R Appendix B: Enough Calculus to Get By [View the detailed Table of Contents](https://nostarch.com/download/samples/BayesianStatisticsTheFunWay_ToC_Sample.pdf) [View the Index](https://nostarch.com/download/samples/BayesianStatisticsTheFunWay_Index_Sample.pdf) Reviews "An excellent introduction to subjects critical to all data scientists." —**Inside Big Data** "The author uses great examples to clarify key concepts . . . I would highly recommend as a supplement for any stats student or professional looking to refresh on Bayesian statistics." **—Stan T., Design Collective** “The book is an excellent introduction, especially for those of us that have a rough time with advanced math but that want to advance in the data science field.” **—NotAMonadTutorial.com** “The writing is no-nonsense, the content is understandable, the examples are engaging, and the Bayesian concepts are explained clearly . . . As a first introduction to Bayesian inference, this book is hard to beat. It nails the key concepts in a compelling and instructive fashion.” **—BayesianSpectacles.org** “A simple yet complete practical introduction to Bayesian inference and statistics.” **—Jose D. Perezgonzalez, Frontiers in Psychology** Extra Stuff Author interview in **[This is not a Monad tutorial](https://notamonadtutorial.com/interview-with-will-kurt-on-his-latest-book-bayesian-statistics-the-fun-way-63ce8aee32ed)**. Featured in **[Great Lakes Geek](http://www.greatlakesgeek.com/other/books/bayesian-statistics.htm)**. Updates View the [**latest errata**](https://nostarch.com/download/errata/BayesianStatistics_errata_p9.pdf).