Making decisions is a ubiquitous mental activity in our private and professional or public lives. It entails choosing one course of action from an available shortlist of options. Statistics for Making Decisions places decision making at the centre of statistical inference, proposing its theory as a new paradigm for statistical practice.
Making decisions is a ubiquitous mental activity in our private and professional or public lives. It entails choosing one course of action from an available shortlist of options. Statistics for Making Decisions places decision making at the centre of statistical inference, proposing its theory as a new paradigm for statistical practice.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Nicholas T. Longford is a Senior Statistician at Imperial College, London, specialising in statistical methods for neonatal medicine. His interests include causal analysis of observational studies, decision theory, and the contest of modelling and design in data analysis. His longer-term appointments in the past include Educational Testing Service, Princeton, NJ, U.S.A., de Montfort University, Leicester, England, and directorship of SNTL, a statistics research and consulting company. He is the author of over 100 journal articles and six other monographs on a variety of topics in applied statistics.
Inhaltsangabe
1 First steps. 2. Statistical paradigms. 3. Positive or negative? 4. Non-normally distributed estimators. 5. Small or large? 6. Study design. 7. Medical screening. 8. Many decisions. 9. Performance of institutions. 10. Clinical trials. 11. Model uncertainty. 12. Postscript.
1 First steps. 2. Statistical paradigms. 3. Positive or negative? 4. Non-normally distributed estimators. 5. Small or large? 6. Study design. 7. Medical screening. 8. Many decisions. 9. Performance of institutions. 10. Clinical trials. 11. Model uncertainty. 12. Postscript.
1 First steps. 2. Statistical paradigms. 3. Positive or negative? 4. Non-normally distributed estimators. 5. Small or large? 6. Study design. 7. Medical screening. 8. Many decisions. 9. Performance of institutions. 10. Clinical trials. 11. Model uncertainty. 12. Postscript.
1 First steps. 2. Statistical paradigms. 3. Positive or negative? 4. Non-normally distributed estimators. 5. Small or large? 6. Study design. 7. Medical screening. 8. Many decisions. 9. Performance of institutions. 10. Clinical trials. 11. Model uncertainty. 12. Postscript.
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