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BL
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| Record Number
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853955
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| Main Entry
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Kurt, Will
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| Title & Author
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Bayesian statistics the fun way : : understanding statistics and probability with Star Wars, LEGO, and rubber ducks /\ by Will Kurt.
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| Publication Statement
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San Francisco :: No Starch Press, Inc.,, [2019]
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, ©2019
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| Page. NO
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1 online resource (1 volume) :: illustrations
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| ISBN
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1098122496
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: 1593279574
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: 9781098122492
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: 9781593279578
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9781593279561
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| Notes
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Includes index.
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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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
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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
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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
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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
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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
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| Abstract
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"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"--
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| Subject
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Bayesian statistical decision theory.
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| Subject
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Probabilities.
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| Subject
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Bayesian statistical decision theory.
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| Subject
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Probabilities.
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| Dewey Classification
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519.5/42
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| LC Classification
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QA279.5
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