Prediction, Diagnosis, and Causal Thinking in Forecasting

Imagine that you lived several thousand years ago and belonged to a tribe of methodologically sophisticated cave-dwellers. Your methodological sophistication is such that you have available to you all present day means of the methodological arsenal—details of the principles of deductive logic, probability theory, access to computational equipment, etc. However, your level of substantive knowledge lags several thousand years behind your methodological sophistication. In particular, you have little knowledge about physics, chemistry, or biology. In recent years, your tribe has noted an alarming decrease in its birth-rate. Furthermore, the tribe’s statistician estimates that unless the trend is shortly reversed, extinction is a real possibility. The tribe’s chief has accordingly launched an urgent project to determine the cause of birth. You are a member of the project team and have been assured that all means, including various forms of experimentation with human subjects, will be permitted to resolve this crucial problem.

[1]  E. Brunswik,et al.  The Conceptual Framework of Psychology , 1954 .

[2]  H. Simon,et al.  Spurious Correlation: A Causal Interpretation* , 1954 .

[3]  K. R. Hammond Probabilistic functioning and the clinical method. , 1955, Psychological review.

[4]  D. Campbell,et al.  EXPERIMENTAL AND QUASI-EXPERIMENT Al DESIGNS FOR RESEARCH , 2012 .

[5]  H. Helson,et al.  Adaptation-level theory , 1964 .

[6]  J. Sawyer,et al.  Measurement and prediction, clinical and statistical. , 1966, Psychological bulletin.

[7]  B. Skinner The phylogeny and ontogeny of behavior , 1966, Behavioral and Brain Sciences.

[8]  E. Brunswik,et al.  The psychology of Egon Brunswik , 1966 .

[9]  D. Campbell Reforms as experiments , 1969 .

[10]  A. Tversky,et al.  Subjective Probability: A Judgment of Representativeness , 1972 .

[11]  R. Howard,et al.  The decision to seed hurricanes. , 1972, Science.

[12]  R. Dawes,et al.  Linear models in decision making. , 1974 .

[13]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[14]  Robert S. Siegler,et al.  Effects of contiguity, regularity, and age on children's causal inferences. , 1974 .

[15]  D. Campbell III. “Degrees of Freedom” and the Case Study , 1975 .

[16]  E. Langer The illusion of control. , 1975 .

[17]  B. Fischhoff,et al.  Hindsight is not equal to foresight: The effect of outcome knowledge on judgment under uncertainty. , 1975 .

[18]  D. N. Sparks,et al.  Data Reduction: Analysing and Interpreting Statistical Data , 1976 .

[19]  Robin M. Hogarth,et al.  Cognitive Processes and the Assessment of Subjective Probability Distributions , 1975 .

[20]  Robert S. Siegler,et al.  The Effects of Simple Necessity and Sufficiency Relationships on Children's Causal Inferences. , 1976 .

[21]  J. Mackie,et al.  The cement of the universe : a study of causation , 1977 .

[22]  David F. Lancy,et al.  Likeness and Likelihood in Everyday Thought: Magical Thinking in Judgments About Personality [and Comments and Reply] , 1977, Current Anthropology.

[23]  B. Fischhoff,et al.  On the Psychology of Experimental Surprises. , 1977 .

[24]  A. Tversky Features of Similarity , 1977 .

[25]  C. B. Barry,et al.  New developments in the applications of Bayesian methods : proceedings of the First European Conference sponsored by the Centre européen d'education permanente (CEDEP) and the Institut européen d'administration des affaires (INSEAD), June 1976 , 1978 .

[26]  R. Hogarth,et al.  Confidence in judgment: Persistence of the illusion of validity. , 1978 .

[27]  P. Killeen Superstition: A Matter of Bias, Not Detectability , 1978, Science.

[28]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[29]  A. Tversky,et al.  Prospect Theory : An Analysis of Decision under Risk Author ( s ) : , 2007 .

[30]  H. J. Einhorn,et al.  Cognitive processes in choice and decision behavior , 1979 .

[31]  T. Cook,et al.  Quasi-experimentation: Design & analysis issues for field settings , 1979 .

[32]  R. Dawes Judgment under uncertainty: The robust beauty of improper linear models in decision making , 1979 .

[33]  A. Ortony Beyond Literal Similarity , 1979 .

[34]  L. Ross,et al.  Human Inference: Strategies and Shortcomings of Social Judgment. , 1981 .

[35]  Steven M. Shugan The Cost Of Thinking , 1980 .

[36]  M. Fishbein Progress in social psychology , 1980 .

[37]  L. Adelman The influence of formal, substantive, and contextual task properties on the relative effectiveness of different forms of feedback in multiple-cue probability learning tasks☆ , 1981 .

[38]  M. Spetch,et al.  Backward conditioning: a reevaluation of the empirical evidence. , 1981, Psychological bulletin.

[39]  Spyros Makridakis,et al.  Forecasting and Planning: An Evaluation , 1981 .

[40]  R. Hogarth Beyond discrete biases: Functional and dysfunctional aspects of judgmental heuristics. , 1981 .

[41]  R. Sternberg,et al.  Evaluation of evidence in causal inference. , 1981 .

[42]  Hillel J. Einhorn,et al.  Judgment under uncertainty: Learning from experience and suboptimal rules in decision making , 1982 .

[43]  Masanao Toda,et al.  Causality, Conditional Probability, and Control , 1982 .

[44]  A. Tversky,et al.  Causal Schemata in Judgments under Uncertainty , 1982 .

[45]  G. A. Miller,et al.  Book Review Nisbett, R. , & Ross, L.Human inference: Strategies and shortcomings of social judgment.Englewood Cliffs, N.J.: Prentice-Hall, 1980. , 1982 .

[46]  Teresa M. Amabile,et al.  Judgment under uncertainty: Informal covariation assessment: Data-based versus theory-based judgments , 1982 .

[47]  Lola L. Lopes Doing the impossible: A note on induction and the experience of randomness. , 1982 .