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Warwick, Jon – International Journal for Mathematics Teaching and Learning, 2015
This paper uses a series of models to illustrate one of the fundamental processes of model building--that of enrichment and elaboration. The paper describes how a problem context is given which allows a series of models to be developed from a simple initial model using a queuing theory framework. The process encourages students to think about the…
Descriptors: Mathematical Models, Mathematics Instruction, Demonstrations (Educational), Statistical Distributions
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Caulfield, Michael J. – Mathematics Teacher, 2012
What if Stephen Douglas instead of Abraham Lincoln had won the U.S. presidential election of 1860? What if John F. Kennedy had not carried some of the eight states he won by 2 percentage points or fewer in 1960? What if six hundred more people in Florida had voted for Al Gore in 2000? And what if, in that same year, the U.S. House of…
Descriptors: Political Campaigns, Elections, Mathematical Models, Mathematical Applications
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Croucher, John S. – Australian Senior Mathematics Journal, 2006
A special but common type of scenario is one in which a company has a promotion that is designed to make the customer purchase more of their product than they otherwise might. Although this can be aimed specifically at children, it really applies to all persons. The basic premise is that the company issues a "set" of different items or…
Descriptors: Problem Solving, Probability, Statistical Distributions, Mathematical Models
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Wild, Chris – Statistics Education Research Journal, 2006
This paper is a personal exploration of where the ideas of "distribution" that we are trying to develop in students come from and are leading to, how they fit together, and where they are important and why. We need to have such considerations in the back of our minds when designing learning experiences. The notion of "distribution" as a lens…
Descriptors: Statistics, Mathematics Instruction, Mathematics Education, Mathematical Concepts
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Konold, Cliff; Harradine, Anthony; Kazak, Sibel – International Journal of Computers for Mathematical Learning, 2007
In current curriculum materials for middle school students in the US, data and chance are considered as separate topics. They are then ideally brought together in the minds of high school or university students when they learn about statistical inference. In recent studies we have been attempting to build connections between data and chance in the…
Descriptors: Middle School Students, Computer Software, Statistical Inference, Statistical Distributions
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Lafouge, Thierry; Laine-Cruzel, Sylvie – Information Processing & Management, 1997
Proposes a mathematical model using the probability formalism to explain why a geometrical law is observed in distributions related to library circulation data. Highlights include techniques based on convolution theory; Lotka's law; and Bradford's law. (Author/LRW)
Descriptors: Geometric Concepts, Library Circulation, Mathematical Formulas, Mathematical Models
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Ferrando, Pere J.; Lorenzo-Seva, Urbano – Educational and Psychological Measurement, 2001
Describes a Windows program for checking the suitability of unidimensional logistic item response models for binary and ordered polytomous responses with respect to a given set of data. The program is based on predicting the observed test score distributions from the item characteristic curves. (SLD)
Descriptors: Computer Software, Item Response Theory, Mathematical Models, Prediction
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Brown, Gordon D. A.; McCormack, Teresa; Smith, Mark; Stewart, Neil – Journal of Experimental Psychology: Human Perception and Performance, 2005
Two experiments examined identification and bisection of tones varying in temporal duration (Experiment 1) or frequency (Experiment 2). Absolute identification of both durations and frequencies was influenced by prior stimuli and by stimulus distribution. Stimulus distribution influenced bisection for both stimulus types consistently, with more…
Descriptors: Stimuli, Statistical Distributions, Mathematical Models, Novelty (Stimulus Dimension)
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Stone, Clement A. – Journal of Educational Measurement, 2000
Describes a goodness-of-fit statistic that considers the imprecision with which ability is estimated and involves constructing item fit tables based on each examinee's posterior distribution of ability, given the likelihood of the response pattern and an assumed marginal ability distribution. Also describes a Monte Carlo resampling procedure to…
Descriptors: Goodness of Fit, Item Response Theory, Mathematical Models, Monte Carlo Methods
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Scheaffer, Richard L. – Mathematics Teacher, 1990
Outlines differences between classical statistics and exploratory data analysis. Provides examples in the use of the exploratory techniques. (YP)
Descriptors: Data Analysis, Evaluation Methods, Graphs, Mathematical Models