Record ID | harvard_bibliographic_metadata/ab.bib.00.20150123.full.mrc:599973693:1770 |
Source | harvard_bibliographic_metadata |
Download Link | /show-records/harvard_bibliographic_metadata/ab.bib.00.20150123.full.mrc:599973693:1770?format=raw |
LEADER: 01770cam a2200301uu 4500
001 000733916-X
005 20090712084102.0
008 840412s1984 caua b 00010 eng
010 $a 84050890
020 $a0803923287 (pbk.) :$c$5.00
035 0 $aocm11615888
040 $aDLC$cDLC
050 0 $aQA279.5$b.I94 1984
060 4 $aQA 279.5$bI94b 1984
082 0 $a519.5/42$219
100 1 $aIversen, Gudmund R.
245 10 $aBayesian statistical inference /$cGudmund R. Iversen.
260 0 $aBeverly Hills :$bSage Publications,$cc1984.
300 $a80 p. :$bill. ;$c22 cm.
490 1 $aSage university papers series. Quantitative applications in the social sciences ;$vno. 07-043
504 $aBibliography: p. 78-79.
505 0 $a1. Thomas Bayes and statistical inference -- 2. Classical statistical inference -- Use of tail probabilities -- Interpretation of confidence intervals -- Uncertainty about parameter values -- 3. Bayes' theorem -- Derivation -- An example -- One population -- 4. Bayesian methods for a proportion -- Proportion -- 5. Bayesian methods for other parameters -- Mean -- Correlation -- Regression -- Contingency tables -- Difference between two means -- Ratio of two variances -- Analysis of variance -- 6. Prior distributions -- Informative versus noninformative priors -- Finding prior distributions -- Subjective nature of priors -- Effect of priors -- 7. Bayesian difficulties -- Priors -- Data probabilities -- Computation -- 8. Bayesian strengths -- Specific reasons -- General reasons.
650 0 $aBayesian statistical decision theory.
690 9 $aStatistical inference.$5soc
650 2 $aBayes Theorem.
830 0 $aQuantitative applications in the social sciences ;$vno. 07-043.
988 $a20020608
906 $0DLC