User:Alexander L. Davis
Contact Info
- Alexander L. Davis
- Carnegie Mellon University
- 5000 Forbes Avenue
- Pittsburgh, PA, United States.
- Email me through OpenWetWare
I work in Social and Decision Sciences at Carnegie Mellon University. I learned about OpenWetWare from Wikipedia and John Miller. My main interest is creativity and hypothesis generation with respect to normative, descriptive, and prescriptive decision-making, focusing on scientific decisions.
Education
- 2012, PhD, Carnegie Mellon University, Behavioral Decision Research
- 2009, MS, Carnegie Mellon University, Behavioral Decision Research
- 2007, BS, Northern Arizona University, Psychology
Research Interests and Lab Notebooks
The File-Drawer Problem (Dissertation)
This dissertation provides normative, descriptive, and prescriptive analyses of a scientist’s decision to share data. The normative analysis (Chapter Two) concludes that, although there is no logical ground for determining whether data or theory is faulty when they conflict, data sharing policies that omit disconfirming data are unethical because they impose conventions on the reader, thus deceiving them. However, five experiments (Chapter Four) find that surprising disconfirmations are perceived to be caused by error, and future observations that are seen as diffuse are judged to be less worthy of publication. The second part of the normative analysis (Chapter Three) concludes that disconfirmations are more likely to be errors than affirmations only when the selection of true hypotheses is common. However, participants in the Wason rule discovery task (Chapter Five), who were asked to discover the rule that generated a set of three numbers (2,4,6), thought the opposite. With no penalty for incorrect error attributions, participants proposed triples that did not fit the rule (false hypotheses) more often than those that did fit the rule, but attributed error more often to disconfirmation than affirmation. Furthermore, they shared data based on their attributions of error, and these error attributions were affected by whether feedback was affirming or disconfirming, even after controlling for whether the data were actually error. The prescriptive analysis (Chapter Six) proposes methods of documenting data, methods, and statistical analyses so that penalties can be implemented when inferences are faulty or documentation is poor. The dissertation concludes with a recapitulation of the normative, descriptive, and prescriptive analyses and highlights directions for future work.
Psychology of Methodology
What are the important psychological aspects of designing, implementing, interpreting, and reporting experimental research?
Human Altruism
How do humans behave when they can prevent harm to others by incurring it on themselves?
Human Behavior and Electricity Consumption
What are the cognitive and motivational factors involved in understanding one's electricity consumption?
- Setting a Standard for Pilot Studies
- In-Home Displays
- Nudgers and Nudgees
- CMU Energy and Behavior Group
Methodology of Psychology
How can prescriptive approaches to scientific research help our cognitive and social limitations? I'm writing a book. Not sure what to call it yet. I'll make it available, for free, and I'd very much appreciate comments, critiques, suggestions or whatever. Since it is free, if you feel inclined to show your gratitude to me financially, I suggest donating to kiva.org or your favorite charity.
Human and Artificial Intelligence
How can human performance be elucidated by comparing it to modern artificial intelligence methods. For examaple, how does human knowledge representation compare to an ontology? Applications include drug discovery.
Courses
Research101
My take on everything you need to know to complete an experimental research project.
Adaptive Pretesting
Adaptive design for pretesting: How can we use adaptive design to develop very strong experiments efficiently? We may want to test our auxiliary assumptions 'online' until they converge into a reasonable risk level.
Stats for Social Sciences
Rest assured there will be no p-values. Cohen et al, applied regression
Advanced Stats
Rest assured there will be no p-values. Cosma's Class; Bayesian Data Analysis; Gelman and Hill;
Intro to Cognitive Psychology
Human thinking, reasoning, perception, etc.
Intro to Social Psychology
Motivation, social cognition, etc.
Intro to Experimental Economics
Real human behavior in microeconomics and game theory. Kagel and Roth: Handbook of Expeirmental Economics; Plott and Smith: Handbook of experiment economics results
Computer Science for Social Sciences
Python, Octave, R; Stats; Complexity Theory; Sipser: Introduction to the theory of computation
Decision Theory
Raiffa; Levi? Seidenfeld; Savage; Ramsey; Berger: Statistical Decision Theory and Bayesian Analysis; Gilboa: Theory of decision under uncertainty; Pratt and Raiffa: Statistical Decision Theory; Kadane (2011; pg. 1-4) has a nice demonstration of how to be a dutch bookie.
Behavioral Decision Research
Normative, Descriptive, Prescriptive; Poulton; K&T; von Winterfeldt and Edwards; Raiffa and Tversky: Decision-Making; Gigerenzer: Adaptive Thinking
Game Theory
Von Neumann and Morgenstern; Luce and Raiffa: Games and Decisions
Behavioral Game Theory
Camerer: Behavioral Game Theory; Builds on Decision Theory with empirical evidence. Prereqs: Decision theory; stats
Computational Cognitive Science
Covers three of the most successful computational models: ACT-R; Church; Connectionist; Anderson: How can the mind exist?
Psychology of Science
Herb Simon; Gorman; Klahr; Wason; Klayman and Ha;Carruthers, Stich and Siegal: The cognitive basis of science
Philosophy of Science
Peirce; Carnap; Wittgenstein; Quine; Duhem; Lakatos; Kuhn; Popper; Van Bovens and Hartmann; Mayo; Suppes;
Machine Learning
MacKay: information theory, inference and learning algorithms; Hastie, Tibshirani and Friedman: The elements of statistical learning; Bishop: Pattern recognition and Machine Learning
Publications
-
Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters
http://www.sciencedirect.com/science/article/pii/S0301421511009244
