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Theil, Henri – Amer J Sociol, 1970
This article is concerned with the specification and estimation of relationships whose dependent variable is qualitative in nature (such as yes or no). It discusses logit equations with and without interaction, and the estimation procedure is generalized least squares. (Author)
Descriptors: Correlation, Data Analysis, Factor Analysis, Probability
Peer reviewedGuttman, Louis – Psychometrika, 1971
Descriptors: Definitions, Item Analysis, Measurement, Multiple Regression Analysis
Fischbein, Efraim; And Others – Child Develop, 1970
Short Instruction enabled third- and sixth-graders to make correct ratio decisions. (MH)
Descriptors: Age Differences, Concept Formation, Instruction, Probability
White, Locke, Jr. – Amer J Phys, 1970
Advocates a simplified procedure for assessing the validity of experimental data. Suggests using the range of the results of a limited number of repeated measurements to obtain confidence limits about the probable over-all average of repeating the same procedure a great many times. Bibliography. (LC)
Descriptors: College Science, Data Analysis, Instruction, Measurement
Peer reviewedFischer, Frederic E. – Mathematics Teacher, 1971
Descriptors: College Mathematics, Instruction, Mathematics, Mathematics Instruction
Peer reviewedWennergren, E. Boyd; Nielsen, Darwin B. – Journal of Leisure Research, 1970
Descriptors: Consumer Economics, Mathematical Models, Probability, Recreational Activities
Peer reviewedCohen, Jacob – Educational and Psychological Measurement, 1970
Descriptors: Hypothesis Testing, Predictive Measurement, Probability, Sampling
Peer reviewedFlory, David W. – Arithmetic Teacher, 1969
Descriptors: Elementary School Mathematics, Instruction, Mathematical Concepts, Probability
Kroll, Neal E. A. – J Exp Psychol, 1970
Descriptors: Cues, Feedback, Learning Processes, Multiple Choice Tests
Peer reviewedShumway, Richard J. – Arithmetic Teacher, 1983
A computer program that allows students to simulate an experiment in probability is given, with specific suggestions on how to use and study the program. (MNS)
Descriptors: Computer Programs, Learning Activities, Mathematics Instruction, Microcomputers
Peer reviewedJohnson, Bruce R. – American Mathematical Monthly, 1983
A way of presenting the Poisson process and deriving the Poisson distribution for upper-division courses in probability or mathematical statistics is presented. The main feature of the approach lies in the formulation of Poisson postulates with immediate intuitive appeal. (MNS)
Descriptors: College Mathematics, Higher Education, Mathematics Instruction, Probability
Peer reviewedTerrell, Colin D. – Educational and Psychological Measurement, 1982
Tables are presented giving the critical values of the biserial and the point biserial correlation coefficients (when the null hypothesis assumes a value of zero for the coefficient) at the 0.05 and the 0.01 levels of significance. (Author)
Descriptors: Correlation, Mathematical Formulas, Probability, Research Tools
Peer reviewedHsu, Louis M. – Educational and Psychological Measurement, 1979
Though the Paired-Item-Score (Eakin and Long) (EJ 174 780) method of scoring true-false tests has certain advantages over the traditional scoring methods (percentage right and right minus wrong), these advantages are attained at the cost of a larger risk of misranking the examinees. (Author/BW)
Descriptors: Comparative Analysis, Guessing (Tests), Objective Tests, Probability
Peer reviewedWilcox, Rand R. – Educational and Psychological Measurement, 1979
The classical estimate of a binomial probability function is to estimate its mean in the usual manner and to substitute the results in the appropriate expression. Two alternative estimation procedures are described and examined. Emphasis is given to the single administration estimate of the mastery test reliability. (Author/CTM)
Descriptors: Cutting Scores, Mastery Tests, Probability, Scores
Marcum, C. Everett – Journal of Physical Education and Recreation, 1981
A model for comparing risks to resources with exposures to hazards is described and then applied to the physical educator. (JMF)
Descriptors: Accident Prevention, Models, Physical Education, Prediction
