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Introduction to Bayesian statistics - Bolstad M.

Bolstad M. Introduction to Bayesian statistics - Wiley Publishing, 2004. - 361 p.
ISBN 0-471-27020-2
Download (direct link): introductiontobayesianstatistics2004.pdf
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probability density function, 113 probability
addition rule, 60 axioms, 59, 71 conditional, 62
independent events, 63 degree of belief, 69 joint, 60
law of total probability, 64, 72 long run relative frequency, 68 marginal, 61
multiplication rule, 63, 72, 90 quartiles
data set, 30, 48
from cumulative frequency polygon, 35 posterior distribution, 139 random experiment, 58, 71 random sampling cluster, 16, 22 simple, 15, 22 stratified, 15, 22 randomization, 5, 10 randomized response methods, 16, 22 range
data set, 42, 49 regression
Bayes’ theorem, 244 least squares, 236
normal equations, 236 simple linear regression assumptions, 241 robust Bayesian methods, 261 sample, 5, 14, 21 sample space, 69, 71 Sample space
of a random experiment, 58 sampling distribution, 7, 10, 23-24, 148 sampling frame, 15 scatterplot, 44, 49, 235 scatterplot matrix, 45 scatterplot matrix, 49 scientific method, 3, 10 role of statistics, 4, 10 standard deviation data set, 44, 49 statistic, 14, 21 statistical inference, 1, 14, 71 statistics, 5
stem-and-leaf diagram, 32, 48 back-to-back, 37 Student’st, 182 Student’s t distribution, 305 critical values, 304 uniform distribution, 116 universe, 58
of a joint experiment, 84 reduced, 62, 65, 88 variance
continuous random variable, 116 data set, 43, 49
difference between ind. RV’s, 88, 92 discrete random variable, 79, 91 grouped data, 43 of a linear function, 80, 91 sumofind. RV’s, 87, 91 Venn diagram, 58, 60
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