The Subjectivity of Scientists and the Bayesian Approach

The Subjectivity of Scientists and the Bayesian Approach
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Artikel-Nr:
9781118150627
Veröffentl:
2012
Einband:
E-Book
Seiten:
304
Autor:
S. James Press
Serie:
1, Wiley Series in Probability and Statistics
eBook Typ:
PDF
eBook Format:
Reflowable E-Book
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:

Comparing and contrasting the reality of subjectivity in the work of history's great scientists and the modern Bayesian approach to statistical analysis Scientists and researchers are taught to analyze their data from an objective point of view, allowing the data to speak for themselves rather than assigning them meaning based on expectations or opinions. But scientists have never behaved fully objectively. Throughout history, some of our greatest scientific minds have relied on intuition, hunches, and personal beliefs to make sense of empirical data-and these subjective influences have often aided in humanity's greatest scientific achievements. The authors argue that subjectivity has not only played a significant role in the advancement of science, but that science will advance more rapidly if the modern methods of Bayesian statistical analysis replace some of the classical twentieth-century methods that have traditionally been taught. To accomplish this goal, the authors examine the lives and work of history's great scientists and show that even the most successful have sometimes misrepresented findings or been influenced by their own preconceived notions of religion, metaphysics, and the occult, or the personal beliefs of their mentors. Contrary to popular belief, our greatest scientific thinkers approached their data with a combination of subjectivity and empiricism, and thus informally achieved what is more formally accomplished by the modern Bayesian approach to data analysis. Yet we are still taught that science is purely objective. This innovative book dispels that myth using historical accounts and biographical sketches of more than a dozen great scientists, including Aristotle, Galileo Galilei, Johannes Kepler, William Harvey, Sir Isaac Newton, Antoine Levoisier, Alexander von Humboldt, Michael Faraday, Charles Darwin, Louis Pasteur, Gregor Mendel, Sigmund Freud, Marie Curie, Robert Millikan, Albert Einstein, Sir Cyril Burt, and Margaret Mead. Also included is a detailed treatment of the modern Bayesian approach to data analysis. Up-to-date references to the Bayesian theoretical and applied literature, as well as reference lists of the primary sources of the principal works of all the scientists discussed, round out this comprehensive treatment of the subject. Readers will benefit from this cogent and enlightening view of the history of subjectivity in science and the authors' alternative vision of how the Bayesian approach should be used to further the cause of science and learning well into the twenty-first century.
Comparing and contrasting the reality of subjectivity in the workof history's great scientists and the modern Bayesian approach tostatistical analysisScientists and researchers are taught to analyze their data from anobjective point of view, allowing the data to speak for themselvesrather than assigning them meaning based on expectations oropinions. But scientists have never behaved fully objectively.Throughout history, some of our greatest scientific minds haverelied on intuition, hunches, and personal beliefs to make sense ofempirical data-and these subjective influences have often aided inhumanity's greatest scientific achievements. The authors argue thatsubjectivity has not only played a significant role in theadvancement of science, but that science will advance more rapidlyif the modern methods of Bayesian statistical analysis replace someof the classical twentieth-century methods that have traditionallybeen taught.To accomplish this goal, the authors examine the lives and work ofhistory's great scientists and show that even the most successfulhave sometimes misrepresented findings or been influenced by theirown preconceived notions of religion, metaphysics, and the occultor the personal beliefs of their mentors. Contrary to popularbelief, our greatest scientific thinkers approached their data witha combination of subjectivity and empiricism, and thus informallyachieved what is more formally accomplished by the modern Bayesianapproach to data analysis.Yet we are still taught that science is purely objective. Thisinnovative book dispels that myth using historical accounts andbiographical sketches of more than a dozen great scientistsincluding Aristotle, Galileo Galilei, Johannes Kepler, WilliamHarvey, Sir Isaac Newton, Antoine Levoisier, Alexander vonHumboldt, Michael Faraday, Charles Darwin, Louis Pasteur, GregorMendel, Sigmund Freud, Marie Curie, Robert Millikan, AlbertEinstein, Sir Cyril Burt, and Margaret Mead. Also included is adetailed treatment of the modern Bayesian approach to dataanalysis. Up-to-date references to the Bayesian theoretical andapplied literature, as well as reference lists of the primarysources of the principal works of all the scientists discussedround out this comprehensive treatment of the subject.Readers will benefit from this cogent and enlightening view of thehistory of subjectivity in science and the authors' alternativevision of how the Bayesian approach should be used to further thecause of science and learning well into the twenty-first century.
Prefaceix1. Introduction 12. Selecting the Scientists 173. Some Well Known Stories of Extreme Subjectivity 233.1 Introduction 233.2 Johannes Kepler 233.3 Gregor Mendel 263.4 Robert Millikan 343.5 Cyril Burt 373.6 Margaret Mead 434. Stories of Famous Scientists 494.1 Introduction 494.2 Aristotle 514.3 Galileo Galilei 604.4 William Harvey 714.5 Sir Isaac Newton 814.6 Antoine Lavoisier 954.7 Alexander von Humboldt 1104.8 Michael Faraday 1214.9 Charles Darwin 1284.10 Louis Pasleur 1434.11 Sigmund Freud 1564.12 Marie Curie 1664.13 Albert Einstein 1774.14 Same Conjecrures About the Scientists 1895. Subjectivity .in Science in Modern Times: The Bayesian Approach199Appendix: References by Field of Application for Bayesian Statistical Science225Bibliography 231Subject Index 249Name Index 267

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