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Bolstad W.M. — Introduction to Bayesian Statistics
Bolstad W.M. — Introduction to Bayesian Statistics



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Название: Introduction to Bayesian Statistics

Автор: Bolstad W.M.

Аннотация:

This textbook is suitable for beginning undergraduates encountering rigorous statistics for the first time. The word "Bayesian" in the title simply indicates that the material is approached from a Bayesian rather than the more traditional frequentist perspective. The basic foundations of statistics are covered: discrete random variables, mean and variance, continuous random variables and common distributions, and so on, as well as a fair amount of specifically Bayesian material, such as chapters on Bayesian inference. As is the norm for elementary statistics books, Bolstad (statistics, University of Waikato, New Zealand) claims this book is suitable for undergraduates with no calculus experience; however, basic familiarity with integral calculus will help students considerably in the sections devoted to continuous random variables.


Язык: en

Рубрика: Математика/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: 2nd edition

Год издания: 2007

Количество страниц: 437

Добавлена в каталог: 22.05.2008

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Quartiles, from cumulative frequency polygon      35
Quartiles, posterior distribution      15 1
Random experiment      58 72
Random sampling, cluster      16 22
Random sampling, simple      15 22
Random sampling, stratified      15 22
Randomization      5 10
Randomized response methods      16 22
Range, data set      42 49
Regression, Bayes' theorem      276
Regression, least squares      268
Regression, normal equations      268
Regression, simple linear regression assumptions      273
Robust Bayesian methods      3 17
Sample      5 14 21
Sample space      69 72
Sample space of a random experiment      58
Sampling distribution      7 11 23—24 162
Sampling frame      15
scatterplot      44 49 267
Scatterplot matrix      45 49
Scientific method      3 10
Scientific method, role of statistics      4 10
Standard deviation, data set      44 49
Statistic      14 21
Statistical inference      1 14 72
Statistics      5
Stem-and-Leaf diagram      32 48
Stem-and-leaf diagram, back-to-back      37
Student's t distribution      212 297 357
Student's t distribution, critical values      366
Uniform distribution      126
Universe      58
Universe of a joint experiment      89
Universe, reduced      62 65 92
Updating rule, binomial proportion $\pi$      145
Updating rule, normal mean $\mu$      208
Updating rule, normal variance $\sigma^2$      303
Updating rule, Poisson parameter $\mu$      186
Variance, continuous random variable      126
Variance, data set      43 49
Variance, difference between ind. RV’s      92 96
Variance, discrete random variable      81 95
Variance, grouped data      43
Variance, linear function      82 96
Variance, sum of ind. RV's      91 96
Venn diagram      58 60
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