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Bayesian statistics the fun way : understanding statistics and probability with Star Wars, LEGO, and rubber ducks /

"An introduction to Bayesian statistics with simple and pop culture-based explanations. Topics covered include measuring your own uncertainty in a belief, applying Bayes' theorem, and calculating distributions"--

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kurt, Will (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: San Francisco : No Starch Press, Inc., [2019]
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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050 4 |a QA279.5  |b .K87 2019 
082 0 4 |a 519.5/42 
049 |a UAMI 
100 1 |a Kurt, Will,  |e author. 
245 1 0 |a Bayesian statistics the fun way :  |b understanding statistics and probability with Star Wars, LEGO, and rubber ducks /  |c by Will Kurt. 
264 1 |a San Francisco :  |b No Starch Press, Inc.,  |c [2019] 
264 4 |c ©2019 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Print version record. 
500 |a Includes index. 
505 0 |a Part 1. Introduction to probability -- Ch. 1. Bayesian thinking and everyday reasoning -- Ch. 2. Measuring uncertainty -- Ch. 3. The logic of uncertainty -- Ch. 4. Creating a binomial probability distribution -- Ch. 5. The beta distribution -- Part 2. Bayesian probability and prior probabilities -- Ch. 6. Conditional probability -- Ch. 7. Bayes' theorem with LEGO -- Ch. 8. The prior, likelihood, and posterior of Bayes' theorem -- Ch. 9. Bayesian priors and working with probability distributions -- Part 3. Parameter estimation -- Ch. 10. Introduction to averaging and parameter estimation -- Ch. 11. Measuring the spread of our data -- Ch. 12. The normal distribution -- Ch. 13. Tools of parameter estimation : the PDF, CDF, and Quantile function -- Ch. 14. Parameter estimation with prior probabilities -- Part 4. Hypothesis testing : the heart of statistics -- Ch. 15. From parameter estimation to hypothesis testing : building a Bayesian A/B test -- Ch. 16. Introduction to the Bayes factor and posterior odds : the competition of ideas -- Ch. 17. Bayesian reasoning in the twilight zone -- Ch. 18. When data doesn't convince you -- Ch. 19. From hypothesis testing to parameter estimation -- Appendix A: A quick introduction to R -- Appendix B: Enough calculus to get by. 
505 0 |a Intro; Brief Contents; Contents in Detail; Acknowledgments; Introduction; Why Learn Statistics?; What Is "Bayesian" Statistics?; What's in This Book; Part I: Introduction to Probability; Part II: Bayesian Probability and Prior Probabilities; Part III: Parameter Estimation; Part IV: Hypothesis Testing: The Heart of Statistics; Background for Reading the Book; Now Off on Your Adventure!; Part I: Introduction to Probability; Chapter 1: Bayesian Thinking and Everyday Reasoning; Reasoning About Strange Experiences; Observing Data; Holding Prior Beliefs and Conditioning Probabilities 
505 8 |a Forming a HypothesisSpotting Hypotheses in Everyday Speech; Gathering More Evidence and Updating Your Beliefs; Comparing Hypotheses; Data Informs Belief; Belief Should Not Inform Data; Wrapping Up; Exercises; Chapter 2: Measuring Uncertainty; What Is a Probability?; Calculating Probabilities by Counting Outcomes of Events; Calculating Probabilities as Ratios of Beliefs; Using Odds to Determine Probability; Solving for the Probabilities; Measuring Beliefs in a Coin Toss; Wrapping Up; Exercises; Chapter 3: The Logic of Uncertainty; Combining Probabilities with AND 
505 8 |a Solving a Combination of Two ProbabilitiesApplying the Product Rule of Probability; Example: Calculating the Probability of Being Late; Combining Probabilities with OR; Calculating OR for Mutually Exclusive Events; Using the Sum Rule for Non-Mutually Exclusive Events; Example: Calculating the Probability of Getting a Hefty Fine; Wrapping Up; Exercises; Chapter 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 
505 8 |a Combinatorics: Advanced Counting with the Binomial CoefficientCalculating the Probability of the Desired Outcome; Example: Gacha Games; Wrapping Up; Exercises; Chapter 5: The Beta Distribution; A Strange Scenario: Getting the Data; Distinguishing Probability, Statistics, and Inference; Collecting Data; Calculating the Probability of Probabilities; The Beta Distribution; Breaking Down the Probability Density Function; Applying the Probability Density Function to Our Problem; Quantifying Continuous Distributions with Integration; Reverse-Engineering the Gacha Game; Wrapping Up; Exercises 
505 8 |a Part II: Bayesian Probability and Prior ProbabilitiesChapter 6: Conditional Probability; Introducing Conditional Probability; Why Conditional Probabilities Are Important; Dependence and the Revised Rules of Probability; Conditional Probabilities in Reverse and Bayes' Theorem; Introducing Bayes' Theorem; Wrapping Up; Exercises; Chapter 7: Bayes' Theorem with LEGO; Working Out Conditional Probabilities Visually; Working Through the Math; Wrapping Up; Exercises; Chapter 8: The Prior, Likelihood, and Posterior of Bayes' Theorem; The Three Parts; Investigating the Scene of a Crime 
520 |a "An introduction to Bayesian statistics with simple and pop culture-based explanations. Topics covered include measuring your own uncertainty in a belief, applying Bayes' theorem, and calculating distributions"--  |c Provided by publisher 
504 |a Includes bibliographical references and index. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Bayesian statistical decision theory. 
650 0 |a Probabilities. 
650 2 |a Probability 
650 6 |a Théorie de la décision bayésienne. 
650 6 |a Probabilités. 
650 7 |a probability.  |2 aat 
650 7 |a Bayesian statistical decision theory.  |2 fast  |0 (OCoLC)fst00829019 
650 7 |a Probabilities.  |2 fast  |0 (OCoLC)fst01077737 
776 0 8 |i Print version:  |a Kurt, Will.  |t Bayesian statistics the fun way.  |d San Francisco : No Starch Press, Inc., [2019]  |z 9781593279561  |w (DLC) 2019020743  |w (OCoLC)1100441088 
856 4 0 |u https://learning.oreilly.com/library/view/~/9781098122492/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
938 |a Askews and Holts Library Services  |b ASKH  |n AH36247501 
938 |a ProQuest Ebook Central  |b EBLB  |n EBL6063015 
994 |a 92  |b IZTAP