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Prodromou, Theodosia; Pratt, Dave – Technology, Knowledge and Learning, 2013
This paper presents a case study of students (age 14-15) as they attempt to make sense of distribution, adopting a range of causal meanings for the variation observed in the animated computer display and in the graphs generated by a "BasketBall" simulation. The student activity is analysed through dimensions of complex causality. The…
Descriptors: Computer Simulation, Junior High School Students, Probability, Statistical Distributions
Students' Informal Inference about the Binomial Distribution of "Bunny Hops": A Dialogic Perspective
Kazak, Sibel; Fujita, Taro; Wegerif, Rupert – Statistics Education Research Journal, 2016
The study explores the development of 11-year-old students' informal inference about random bunny hops through student talk and use of computer simulation tools. Our aim in this paper is to draw on dialogic theory to explain how students make shifts in perspective, from intuition-based reasoning to more powerful, formal ways of using probabilistic…
Descriptors: Inferences, Computer Simulation, Probability, Statistical Distributions
Conant, Darcy Lynn – ProQuest LLC, 2013
Stochastic understanding of probability distribution undergirds development of conceptual connections between probability and statistics and supports development of a principled understanding of statistical inference. This study investigated the impact of an instructional course intervention designed to support development of stochastic…
Descriptors: Statistics, Probability, Statistical Distributions, Statistical Inference
Jarrell, Michele G. – 1991
A probability distribution was developed for the Andrews-Pregibon (AP) statistic. The statistic, developed by D. F. Andrews and D. Pregibon (1978), identifies multivariate outliers. It is a ratio of the determinant of the data matrix with an observation deleted to the determinant of the entire data matrix. Although the AP statistic has been used…
Descriptors: Computer Simulation, Error of Measurement, Matrices, Multivariate Analysis
Ware, William B.; Althouse, Linda Akel – 1999
This study was designed to derive the distribution of a test statistic based on normal probability plots. The first purpose was to provide an empirical derivation of the critical values for the Line Test (LT) with an extensive computer simulation. The goal was to develop a test that is sensitive to a wide range of alternative distributions,…
Descriptors: Computation, Computer Simulation, Monte Carlo Methods, Probability
Lee, Won-Chan; Brennan, Robert L.; Kolen, Michael J. – Journal of Educational and Behavioral Statistics, 2006
Assuming errors of measurement are distributed binomially, this article reviews various procedures for constructing an interval for an individual's true number-correct score; presents two general interval estimation procedures for an individual's true scale score (i.e., normal approximation and endpoints conversion methods); compares various…
Descriptors: Probability, Intervals, Guidelines, Computer Simulation

Snijders, Tom A. B. – Psychometrika, 1991
A complete enumeration method and a Monte Carlo method are presented to calculate the probability distribution of arbitrary statistics of adjacency matrices when these matrices have the uniform distribution conditional on given row and column sums, and possibly on a given set of structural zeros. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Mathematical Models, Matrices

Schilling, Mark F. – College Mathematics Journal, 1990
Developed are simple recursion formulas for generating the exact distribution of the longest run of heads, both for a fair coin and for a biased coin. Discusses the applications of runs-related phenomena such as molecular biology, Markov chains, geometric variables, and random variables. (YP)
Descriptors: College Mathematics, Computer Simulation, Higher Education, Mathematical Applications

Wilcox, Rand R. – Psychometrika, 1993
Modifications are proposed to the recently developed method of comparing one-step M-estimators of location corresponding to two independent groups that provides good control over the probability of Type I error even for unequal sample size, unequal variances, and different shaped distributions. Simulation results reveal cautions required. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)

Arnold, Barry C.; And Others – Psychometrika, 1993
Inference is considered for the marginal distribution of "X" when ("X", "Y") has a truncated bivariate normal distribution. The "Y" variable is truncated, but only the "X" values are observed. A sample of 87 Otis test scores is shown to be well described by this model. (SLD)
Descriptors: Admission (School), Computer Simulation, Equations (Mathematics), Mathematical Models
Prodromou, Theodosia; Pratt, Dave – Statistics Education Research Journal, 2006
Our primary goal is to design a micro world which aspires to research thinking-in-change about distribution. Our premise, in line with a constructivist approach and our prior research, is that thinking about distribution must develop from causal meanings already established. This study reports on a design research study of how students appear to…
Descriptors: Constructivism (Learning), Secondary School Students, Foreign Countries, Computer Software