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Pillay, Seshini; Buffler, Andy; Lubben, Fred; Allie, Saalih – European Journal of Physics, 2008
An evaluation of a course aimed at developing university students' understanding of the nature of scientific measurement and uncertainty is described. The course materials follow the framework for metrology as recommended in the "Guide to the Expression of Uncertainty in Measurement" (GUM). The evaluation of the course is based on…
Descriptors: Physics, Laboratory Experiments, Teaching Methods, Probability
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Russell, Beth S.; Trudeau, Jeremiah; Britner, Preston A. – Child Abuse & Neglect: The International Journal, 2008
Purpose: The current study sought to compare interventional materials intended to raise public awareness of the caregiving practices connected to Shaken Baby Syndrome (SBS). Two hundred and sixty four adults (mean age 32 years) were recruited for participation through convenience sampling at a large Northeastern university. Participants fell into…
Descriptors: Intervention, Head Injuries, Factor Analysis, Instructional Materials
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Danielson, Christopher; Jenson, Eric – Mathematics Teacher, 2008
The Wednesday before Thanksgiving presents a challenge to teachers in many U.S. schools. Some students are absent because they are traveling to be with their extended families for the holiday. Other students, assuming that nothing important will happen at school when so many of their peers are absent, may also be absent. One school's solution to…
Descriptors: High School Students, Probability, Teaching Methods, Handheld Devices
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Saelen, Cecile; Markovits, Henry – Journal of Experimental Child Psychology, 2008
This study examined the idea that expectations of behavior in hypothetical situations involving potential moral transgressions are related to emotion attributions relating to both moral and cost-benefit considerations. We asked younger (14 years 5 months) and older (16 years 1 month) female and male adolescents (a) to make predictions about the…
Descriptors: Adolescents, Probability, Fear, Anxiety
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Laming, Donald – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
This article reports some calculations on free-recall data from B. Murdock and J. Metcalfe (1978), with vocal rehearsal during the presentation of a list. Given the sequence of vocalizations, with the stimuli inserted in their proper places, it is possible to predict the subsequent sequence of recalls--the predictions taking the form of a…
Descriptors: Probability, Stimuli, Recall (Psychology), Prediction
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Wakslak, Cheryl J.; Trope, Yaacov; Liberman, Nira; Alony, Rotem – Journal of Experimental Psychology: General, 2006
Conceptualizing probability as psychological distance, the authors draw on construal level theory (Y. Trope & N. Liberman, 2003) to propose that decreasing an event's probability leads individuals to represent the event by its central, abstract, general features (high-level construal) rather than by its peripheral, concrete, specific features…
Descriptors: Probability, Object Permanence, Cognitive Processes, Theories
Holland, Paul W. – 1993
The failure of Hume's "constant conjunction" to describe apparently causal relations in science and everyday life has led to various "probabilistic" theories of causation of which the study by P. C. Suppes (1970) is an important example. A formal model that was developed for the analysis of comparative agricultural experiments…
Descriptors: Causal Models, Probability, Social Science Research
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Shuford, Emir; Brown, Thomas A. – Instructional Science, 1975
Report describes the rationale underlying a procedure for eliciting personal estimates of probabilities utilizing a proper scoring rule, and illustrates some new techniques for calibrating those probabilities and providing better feedback to students learning to assess uncertainty. (Author)
Descriptors: Ambiguity, Educational Research, Individual Development, Probability
Edington, Eugene S. – J Psychol, 1969
Descriptors: Probability, Psychological Testing, Research, Sampling
Harvard Univ., Cambridge, MA. Graduate School of Education. – 1966
THIS BIBLIOGRAPHY SUPPLEMENT LISTS MATERIALS ON VARIOUS ASPECTS OF ACHIEVEMENT. APPROXIMATELY 60 REFERENCES ARE PROVIDED TO DOCUMENTS DATING FROM 1961 TO 1966. JOURNALS, BOOKS, AND REPORT MATERIALS ARE LISTED. SUBJECT AREAS INCLUDED ARE ACHIEVEMENT LEVEL, ACADEMIC ACHIEVEMENT, ACHIEVEMENT MOTIVATION, UNDERACHIEVERS, PROBABILITY ESTIMATES, AND…
Descriptors: Academic Achievement, Achievement, Bibliographies, Probability
Brown, Thomas A. – 1974
The defining property of an admissible scoring system is that any individual perceives himself as maximizing his expected score by reporting his true subjective distribution. The use of admissible scoring systems as a measure of probabilistic forecasts is becoming increasingly well-known in those cases where the forecast is a discrete distribution…
Descriptors: Mathematical Models, Prediction, Probability, Scoring
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Smith, Robert A.; And Others – Educational and Psychological Measurement, 1977
A FORTRAN computer program is described which computes F ratios and attendant probabilities for two-factor fixed effects analysis of variance designs with disproportional cell frequencies. The number of levels for each factor is limited to five and all zero values are considered to be equivalent to missing values. (Author/JKS)
Descriptors: Analysis of Variance, Computer Programs, Probability
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Keselman, H. J.; And Others – Educational and Psychological Measurement, 1976
Compares the harmonic mean and Kramer unequal group forms of the Tukey test for various: (a) degrees of disparate group sizes, (b) numbers of groups, and (c) nominal significant levels. (RC)
Descriptors: Comparative Analysis, Probability, Sampling, Statistical Significance
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Robertson, S. E. – Journal of Documentation, 1977
The principle that, for optimal retrieval, documents should be ranked in order of the probability of relevance is discussed. (Author/KP)
Descriptors: Information Retrieval, Probability, Relevance (Information Retrieval)
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Johnson, David E. – Teaching of Psychology, 1986
Describes a sampling demonstration, using random numbers generated on a microcomputer, that helps to make the central limit theorem concrete and understandable. (Author/JDH)
Descriptors: College Instruction, Demonstrations (Educational), Probability, Sampling
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