Introduction to Statistical Decision Theory Book

	Preface
1	Introduction	1
2	An Informal Treatment of Foundations	11
3	A Formal Treatment of Foundations	47
4	Assessment of Utilities for Consequences	69
5	Quantification of Judgments	93
6	Analysis of Decision Trees	113
7	Random Variables	133
8	Continuous Lotteries and Expectations	159
9	Special Univariate Distributions	181
10	Conditional Probability and Bayes' Theorem	211
11	Bernoulli Process	225
12	Terminal Analysis: Opportunity Loss and the Value of Perfect Information	247
13	Paired Random Variables	273
14	Preposterior Analysis: The Value of Sample Information	307
15	Poisson Process	345
16	Normal Process with Known Variance	375
17	Normal Process with Unknown Variance	417
18	Large Sample Theory	437
19	Statistical Analysis in Normal Form	463
20	Classical Methods	517
21	Multivariate Random Variables	551
22	The Multivariate Normal Distribution	585
23A	Choosing the Best of Several Processes	639
23B	Allowance for Uncertain Bias	655
23C	Stratification	689
23D	The Portfolio Problem	713
24	Normal Linear Regression with Known Variance	731
	Appendix 1: The Terminology of Sets	781
	Appendix 2: Elements of Matrix Theory	785
	Appendix 3: Properties of Utility Functions for Monetary Consequences	805
	Appendix 4: Tables	819
	Bibliography	861
	Index	865