LEADER 02219oam 2200469I 450 001 9910793769503321 005 20190820011803.0 010 $a1-351-62138-6 010 $a1-315-11222-1 010 $a1-351-62139-4 035 $a(CKB)4100000008701571 035 $a(MiAaPQ)EBC5824690 035 $a(OCoLC)1108619516 035 $a(OCoLC-P)1108619516 035 $a(FlBoTFG)9781315112220 035 $a(EXLCZ)994100000008701571 100 $a20190715h20202020 uy 0 101 0 $aeng 135 $aurcnu---unuuu 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntroduction to statistical decision theory $eutility theory and causal analysis /$fSilvia Bacci, Bruno Chiandotto 210 1$aBoca Raton, FL :$cCRC Press,$d2020. 210 4$dİ2020 215 $a1 online resource (305 pages) 311 $a1-138-08356-9 320 $aIncludes bibliographical references and index. 330 $aIntroduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and uncertainty Illustrates expected utility theory and its extensions Describes approaches to elicit the utility function Reviews classical and Bayesian approaches to statistical inference based on decision theory Discusses the role of causal analysis in statistical decision theory 606 $aStatistical decision 606 $aDecision making 615 0$aStatistical decision. 615 0$aDecision making. 676 $a519.542 700 $aBacci$b Silvia$0769875 702 $aChiandotto$b Bruno 801 0$bOCoLC-P 801 1$bOCoLC-P 906 $aBOOK 912 $a9910793769503321 996 $aIntroduction to statistical decision theory$93715890 997 $aUNINA