Ward Edwards
Biographic Data
| ID | 3884514 |
|---|---|
| NAME | Ward Edwards |
| GIVEN NAMES | Ward |
| FAMILY NAME | Edwards |
| SIGNATURE | EDWARDS W |
| AFFILIATIONS | University of Southern California |
| VERIFIED | No |
| TOTAL WORKS | 16 |
| TOTAL CITATIONS | 123 |
| AUTHOR COUNT | 16 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1950 |
| LATEST PUBLICATION YEAR | 2008 |
| H-INDEX | 3 |
A science of decision making: The legacy of Ward Edwards
"Ward Edwards is well known as the father of behavioral decision making. In this book, 29 of Ward Edwards's most important published papers are reprinted, a selection that spans six decades, allowing the reader to see how this creative thinker generated many of the ideas that are now core beliefs among current researchers." "It is perhaps less well known that Edwards continued to make substantial contributions during the years after his retiremen…
Hailfinder: Tools for and experiences with Bayesian normative modeling
Hailfinder: Tools for and experiences with Bayesian normative modeling
Bayes Nets (BNs) and Influence Diagrams (IDs), new tools that use graphic user interfaces to facilitate representation of complex inference and decision structures, will be the core elements of new computer technologies that will make the 21st century the Century of Bayes. BNs are a way of representing a set of related uncertainties. They facilitate Bayesian inference by separating structural information from parameters. Hailfinder is a BN that p…
K out of N; finally, the answers
Murder and (of?) the likelihood principle: A Trialogue
The Likelihood Principle of Bayesian inference asserts that only likelihoods matter to single‐stage inference. A likelihood is the probability of evidence given a hypothesis multiplied by a positive constant. The constant cancels out of simple versions of Bayes's Theorem, and so is irrelevant to single‐stage inferences. Most non‐statistical inferences require a multi‐stage path from evidence to hypotheses; testimony that an event occurred does no…
Evaluation, Thaumaturgy, and Multiattribute Utility Measurement
Conservatism in human information processing
An abundance of research has shown that human beings are conservative processors of fallible information. Such experiments compare human behavior with the outputs of Bayes's theorem, the formally optimal rule about how opinions (that is, probabilities) should be revised on the basis of new information. It turns out that opinion change is very orderly, and usually proportional to numbers calculated from Bayes's theorem – but it is insufficient in …
Costs and payoffs in perceptual research
A persistent problem in psychological research that reaches conclusions about inaccessible processes or experiences inside a subject's head is to validate those conclusions--that is, to exhibit persuasive reasons to believe that emitted behavior in some sense faithfully reports inaccessible processes. In the mid-1950s, perceptual researchers widely adopted an approach that might be called validation by cupidity. If the experimenter is willing to …
Costs and payoffs in perceptual research
Public Values: Multiattribute-Utility Measurement for Social Decision Making
Tactical note on the relation between scientific and statistical hypotheses
Bayesian statistical inference for psychological research.
Bayesian statistics, a currently controversial viewpoint concerning statistical inference, is based on a definition of probability as a particular measure of the opinions of ideally consistent people. Statistical inference is modification of these opinions in the light of evidence, and Bayes’ theorem specifies how such modifications should be made. The tools of Bayesian statistics include the theory of specific distributions and the principle of …
Utility, subjective probability, their interaction, and variance preferences
Peer Reviewed
Behavioral Decision Theory
Behavioral Decision Theory, Page 1 of 1 /docserver/preview/fulltext/psych/12/1/annurev.ps.12.020161.002353-1.gif
The theory of decision making
This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory of riskless choices to welfare economics, the theory of risky choices, transitivity of choices, and the theory of games and statistical decision functions. The theories surveyed assume rational behavior: individu…
Recent research on pain perception
The theory of decision making
This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory of riskless choices to welfare economics, the theory of risky choices, transitivity of choices, and the theory of games and statistical decision functions. The theories surveyed assume rational behavior: individu…
Tactical note on the relation between scientific and statistical hypotheses
Utility, subjective probability, their interaction, and variance preferences
Peer Reviewed
Recent research on pain perception
The theory of decision making
This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory of riskless choices to welfare economics, the theory of risky choices, transitivity of choices, and the theory of games and statistical decision functions. The theories surveyed assume rational behavior: individu…
Behavioral Decision Theory
Behavioral Decision Theory, Page 1 of 1 /docserver/preview/fulltext/psych/12/1/annurev.ps.12.020161.002353-1.gif
Utility, subjective probability, their interaction, and variance preferences
Peer Reviewed
Bayesian statistical inference for psychological research.
Bayesian statistics, a currently controversial viewpoint concerning statistical inference, is based on a definition of probability as a particular measure of the opinions of ideally consistent people. Statistical inference is modification of these opinions in the light of evidence, and Bayes’ theorem specifies how such modifications should be made. The tools of Bayesian statistics include the theory of specific distributions and the principle of …
Tactical note on the relation between scientific and statistical hypotheses
Public Values: Multiattribute-Utility Measurement for Social Decision Making
Conservatism in human information processing
An abundance of research has shown that human beings are conservative processors of fallible information. Such experiments compare human behavior with the outputs of Bayes's theorem, the formally optimal rule about how opinions (that is, probabilities) should be revised on the basis of new information. It turns out that opinion change is very orderly, and usually proportional to numbers calculated from Bayes's theorem – but it is insufficient in …
Costs and payoffs in perceptual research
A persistent problem in psychological research that reaches conclusions about inaccessible processes or experiences inside a subject's head is to validate those conclusions--that is, to exhibit persuasive reasons to believe that emitted behavior in some sense faithfully reports inaccessible processes. In the mid-1950s, perceptual researchers widely adopted an approach that might be called validation by cupidity. If the experimenter is willing to …
Costs and payoffs in perceptual research
Evaluation, Thaumaturgy, and Multiattribute Utility Measurement
Murder and (of?) the likelihood principle: A Trialogue
The Likelihood Principle of Bayesian inference asserts that only likelihoods matter to single‐stage inference. A likelihood is the probability of evidence given a hypothesis multiplied by a positive constant. The constant cancels out of simple versions of Bayes's Theorem, and so is irrelevant to single‐stage inferences. Most non‐statistical inferences require a multi‐stage path from evidence to hypotheses; testimony that an event occurred does no…
K out of N; finally, the answers
Hailfinder: Tools for and experiences with Bayesian normative modeling
Hailfinder: Tools for and experiences with Bayesian normative modeling
Bayes Nets (BNs) and Influence Diagrams (IDs), new tools that use graphic user interfaces to facilitate representation of complex inference and decision structures, will be the core elements of new computer technologies that will make the 21st century the Century of Bayes. BNs are a way of representing a set of related uncertainties. They facilitate Bayesian inference by separating structural information from parameters. Hailfinder is a BN that p…
A science of decision making: The legacy of Ward Edwards
"Ward Edwards is well known as the father of behavioral decision making. In this book, 29 of Ward Edwards's most important published papers are reprinted, a selection that spans six decades, allowing the reader to see how this creative thinker generated many of the ideas that are now core beliefs among current researchers." "It is perhaps less well known that Edwards continued to make substantial contributions during the years after his retiremen…
Psychology (12 works) · Computer Science (9 works) · Cognitive psychology (7 works) · Mathematics (6 works) · Social Psychology (6 works) · Bayesian probability (5 works) · Artificial Intelligence (4 works) · Artificial Intelligence (4 works) · Decision-Making and Behavioral Economics (4 works) · Econometrics (4 works)