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Zatzkis, Henry – Mathematics Teacher, 1974
Descriptors: Diagrams, Geometric Concepts, Mathematical Concepts, Mathematical Formulas
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Kepner, James L. – Mathematics Teacher, 1974
Descriptors: Algebra, Instruction, Mathematical Concepts, Mathematical Formulas
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Greitzer, Samuel L. – Mathematics Teacher, 1972
Descriptors: Geometric Concepts, Instruction, Mathematical Formulas, Mathematics Education
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Gross, Alan L. – Educational and Psychological Measurement, 1982
It is generally believed that the correction formula will yield exact correlational values only when the regression of z on x is both linear and homoscedastic. The formula is shown to hold for nonlinear heteroscedastic relationships. A simple sufficient condition for formula validity and estimation predictions is demonstrated in a numerical…
Descriptors: Correlation, Data Analysis, Mathematical Formulas, Predictor Variables
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Garvin, Alfred D. – Journal of Educational Measurement, 1976
A simple, usefully accurate approximation of the standard error of measurement is proposed for use by classroom teachers. An empirical comparison with Lord's approximation indicated that, though not as easy to calculate as Lord's, this approximation is more practical because it is useful at any point in the score distribution. (BW)
Descriptors: Error of Measurement, Estimation (Mathematics), Mathematical Formulas, Statistical Analysis
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Livingston, Samuel A. – Journal of Educational Measurement, 1982
For tests used to make pass/fail decisions, the relevant standard error of measurement (SEM) is the SEM at the passing score. If the test is highly stratified, this SEM should be estimated by a split-halves approach. A formula and its derivation are provided. (Author)
Descriptors: Cutting Scores, Error of Measurement, Estimation (Mathematics), Mathematical Formulas
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Stavig, Gordon R. – Perceptual and Motor Skills, 1982
The normalized mean is developed and discussed as a descriptive measure of central location. The advantages of the normalized mean over the arithmetic mean, median, and trimmed mean are discussed. (Author)
Descriptors: Mathematical Formulas, Research Problems, Scores, Statistical Analysis
Burton, Robert S. – New Directions for Testing and Measurement, 1980
Although Model A, the only norm-referenced evaluation procedure in the Title I Evaluation and Reporting System, requires no data other than the test scores themselves, it introduces two sources of bias and involved three test administrations. Roberts' two-test procedure offers the advantages of less bias and less testing. (RL)
Descriptors: Comparative Analysis, Mathematical Formulas, Scores, Statistical Bias
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Kahneman, Daniel; Tversky, Amos – Cognition, 1979
Cohen's (TM 504 890) formal rules of intuitive probability lack normative or descriptive appeal, and his interpretation of the author's findings is not compelling. (CP)
Descriptors: Abstract Reasoning, Logical Thinking, Mathematical Formulas, Prediction
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Huynh, Huynh – Journal of Educational Statistics, 1979
In mastery testing, the raw agreement index and the kappa index may be estimated via one test administration when the test scores follow beta-binomial distributions. This paper reports formulae, tables, and a computer program which facilitate the computation of the standard errors of the estimates. (Author/CTM)
Descriptors: Computer Programs, Cutting Scores, Decision Making, Mastery Tests
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Sklar, Michael G. – Journal of Educational Statistics, 1980
It has long been popular to utilize the least squares estimation procedure for fitting the multiple linear regression model to observed data. In this paper, two useful alternatives to least squares estimation in exploratory data analysis are examined: least absolute value estimation and Chebychev estimation. (Author/JKS)
Descriptors: Data Analysis, Least Squares Statistics, Linear Programing, Mathematical Formulas
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Klastorin, T. D. – Psychometrika, 1980
The problem of objectively comparing two independently determined partitions of N objects or variables is discussed. A similarity measure based on the simple matching coefficient is defined and related to previously suggested measures. (Author/JKS)
Descriptors: Correlation, Data Analysis, Judges, Mathematical Formulas
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Cohen, Jacob; Vijverberg, Wim – Journal of the American Society for Information Science, 1980
Considers the application of game theory to library networks in two areas: the development of a systematic way to study individual coalitions, and the stability of the network. (FM)
Descriptors: Game Theory, Interlibrary Loans, Library Cooperation, Library Networks
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Brake, Mary L. – Physics Teacher, 1981
Describes physics formulas which can be used by law enforcement officials to determine the possible velocity of vehicles involved in traffic accidents. These include, among others, the slide to stop-level road, slide to stop-sloping roadway, and slide to stop-two different surfaces formulas. (JN)
Descriptors: Accidents, Investigations, Mathematical Formulas, Motion
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Hopkins, Kenneth D. – Journal of Experimental Education, 1979
Formulas are derived for computing the chi-square statistic from proportions or percentages, both for tests of goodness of fit and association. Advantages of the new formulas are given, as are some examples. (Author/MH)
Descriptors: Expectancy Tables, Goodness of Fit, Mathematical Formulas, Percentage
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