Bayesian statistics the fun way : understanding statistics and probability with Star Wars, LEGO, and rubber ducks / by Will Kurt.
"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"--
Saved in:
| Online Access: |
Full Text (via O'Reilly/Safari) |
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| Main Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
San Francisco :
No Starch Press, Inc.,
[2019]
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| Subjects: |
MARC
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| 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 volume |b nc |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. | ||
| 650 | 0 | |a Bayesian statistical decision theory. | |
| 650 | 0 | |a Probabilities. | |
| 650 | 7 | |a Bayesian statistical decision theory |2 fast | |
| 650 | 7 | |a Probabilities |2 fast | |
| 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 |
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