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Book Categories |
Preface | ||
1 | Introduction to statistical science | 1 |
2 | Scientific data gathering | 13 |
3 | Displaying and summarizing data | 29 |
4 | Logic, probability, and uncertainty | 55 |
5 | Discrete random variables | 75 |
6 | Bayesian inference for discrete random variables | 95 |
7 | Continuous random variables | 111 |
8 | Bayesian inference for binomial proportion | 129 |
9 | Comparing Bayesian and frequentist inferences for proportion | 147 |
10 | Bayesian inference for normal mean | 169 |
11 | Comparing Bayesian and frequentist inferences for mean | 193 |
12 | Bayesian inference for difference between means | 209 |
13 | Bayesian inference for simple linear regression | 235 |
14 | Robust Bayesian methods | 261 |
A | Introduction to calculus | 275 |
B | Use of statistical tables | 295 |
C | Using the included minitab macros | 307 |
D | Using the included R functions | 317 |
E: Answers to selected exercises | 329 | |
References | 349 | |
Index | 351 |
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Add Understanding Computational Bayesian Statistics, Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of t, Understanding Computational Bayesian Statistics to your collection on WonderClub |