Preface. I. BASICS. 1. Introduction to Bayesian Networks. 2. More DAG/Probability Relationships. II. INFERENCE. 3. Inference: Discrete Variables. 4. More Inference Algorithms. 5. Influence Diagrams. III. LEARNING. 6. Parameter Learning: Binary Variables. 7. More Parameter Learning. 8. Bayesian Structure Learning. 9. Approximate Bayesian Structure Learning. 10. Constraint-Based Learning. 11. More Structure Learning. IV. APPICATIONS. 12. Applications. Bibliography. Index.

Learning Bayesian networks

Should one do a component analysis or a factor analysis? The choice is not obvious, because the two broad classes of procedures serve a similar purpose, and share many important mathematical characteristics. Despite many textbooks describing common factor analysis as the preferred procedure, principal component analysis has been the most widely applied. Here we summarize relevant information for the prospective factor/component analyst. First, we discuss the key algebraic similarities and differences. Next, we analyze a number of theoretical and practical issues. The more practical aspects include: the degree of numeric similarity between solutions from the two methods, some common rules for the number of factors to be retained, effects resulting from overextraction, problems with improper solutions, and comparisons in computational efficiency. Finally, we review some broader theoretical issues: the factor indeterminacy issue, the differences between exploratory and confirmatory procedures, and the issue ...

Component Analysis versus Common Factor Analysis: Some issues in Selecting an Appropriate Procedure.

Most academic psychologists do not yet accept the existence of psi, anomalous processes of information or energy transfer (such as telepathy or other forms of extrasensory perception) that are currently unexplained in terms of known physical or biological mechanisms. We believe that the replication rates and effect sizes achieved by one particular experimental method, the ganzfeld procedure, are now sufficient to warrant bringing this body of data to the attention of the wider psychological community. Competing meta-analyses of the ganzfeld database are reviewed, 1 by R. Hyman (1985), a skeptical critic of psi research, and the other by C. Honorton (1985), a parapsychologist and major contributor to the ganzfeld database. Next the results of 11 new ganzfeld studies that comply with guidelines jointly authored by R. Hyman and C. Honorton (1986) are summarized. Finally, issues of replication and theoretical explanation are discussed. The term psi denotes anomalous processes of information or energy transfer, processes such as telepathy or other forms of extrasensory perception that are currently unexplained in terms of known physical or biological mechanisms. The term is purely descriptive: It neither implies that such anomalous phenomena are paranormal nor connotes anything about their underlying mechanisms. Does psi exist? Most academic psychologists don't think so. A survey of more than 1,100 college professors in the United States found that 55% of natural scientists, 66% of social scientists (excluding psychologists), and 77% of academics in the arts, humanities, and education believed that ESP is either an established fact or a likely possibility. The comparable figure for psy

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Does psi exist? Replicable evidence for an anomalous process of information transfer.

Parapsychology, the laboratory study of psychic phenomena, has had its history interwoven with that of statistics. Many of the controversies in parapsychology have focused on statistical issues, and statistical models have played an integral role in the experimental work. Recently, parapsychologists have been using meta-analysis as a tool for synthesizing large bodies of work. This paper presents an overview of the use of statistics in parapsychology and offers a summary of the meta-analyses that have been conducted. It begins with some anecdotal information about the involvement of statistics and statisti- cians with the early history of parapsychology. Next, it is argued that most nonstatisticians do not appreciate the connection between power and "successful" replication of experimental effects. Returning to para- psychology, a particular experimental regime is examined by summariz- ing an extended debate over the interpretation of the results. A new set of experiments designed to resolve the debate is then reviewed. Finally, meta-analyses from several areas of parapsychology are summarized. It is concluded that the overall evidence indicates that there is an anoma- lous effect in need of an explanation.

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Replication and Meta-Analysis in Parapsychology

For more than 100 years, scientists have attempted to determine the truth or falsity of claims for the existence of a perceptual channel whereby certain individuals are able to perceive and describe remote data not presented to any known sense This paper presents an outline of the history of scientific inquiry into such so-called paranormal perception and surveys the current state of the art in parapsychological research in the United States and abroad The nature of this perceptual channel is examined in a series of experiments carried out in the Electronics and Bioengineering Laboratory of Stanford Research Institute The perceptual modality most extensively investigated is the ability of both experienced subjects and inexperienced volunteers to view, by innate mental processes, remote geographical or technical targets including buildings, roads, and laboratory apparatus The accumulated data indicate that the phenomenon is not a sensitive function of distance, and Faraday cage shielding does not in any apparent way degrade the quality and accuracy of perception On the basis of this research, some areas of physics are suggested from which a description or explanation of the phenomenon could be forthcoming

Comments on "A perceptual channel for information transfer over kilometer distances: Historical perspective and recent research"

An experimenter threw individually 219 different dice of four different brands and recorded even and odd outcomes for one block of 20,000 trials for each die—4,380,000 throws in all. The resulting data on runs offer a basis for comparing the observed properties of such a physical randomizing process with theory and with simulations based on pseudo-random numbers and RAND Corporation random numbers. Although generally the results are close to those forecast by theory, some notable exceptions raise questions about the surprise value that should be associated with occurrences two standard deviations from the mean. These data suggest that the usual significance level may well actually be running from 7 to 15 percent instead of the theoretical 5 percent.

Willard H. Longcor

Papers

Bias and runs in dice throwing and recording: A few million throws