具体描述
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 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 shower, 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
作者简介
Will Kurt currently works as a Senior Data Scientist at Bombora, 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. Will is the author of Get Programming with Haskell (Manning Publications) and lives in Reno, Nevada.
目录信息
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
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
Appendix C: Answers to Exercises
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一个原本是英语专业的统计学家把复杂的数学问题解释的小白也能读懂，而且是有意思、有深度的读懂。强力推荐想理解贝叶斯统计在现实中的强大应用的同学们。
评分3.5。基本上是本数学书，讲贝叶斯的基本概念。
评分一个原本是英语专业的统计学家把复杂的数学问题解释的小白也能读懂，而且是有意思、有深度的读懂。强力推荐想理解贝叶斯统计在现实中的强大应用的同学们。
评分3.5。基本上是本数学书，讲贝叶斯的基本概念。
评分一个原本是英语专业的统计学家把复杂的数学问题解释的小白也能读懂，而且是有意思、有深度的读懂。强力推荐想理解贝叶斯统计在现实中的强大应用的同学们。
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