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Griffiths, Martin – International Journal of Mathematical Education in Science and Technology, 2013
We consider here the problem of calculating the moments of binomial random variables. It is shown how formulae for both the raw and the central moments of such random variables may be obtained in a recursive manner utilizing Stirling numbers of the first kind. Suggestions are also provided as to how students might be encouraged to explore this…
Descriptors: Statistics, Statistical Distributions, Probability, Computation
Wulff, Shaun S.; Robinson, Timothy J. – Journal of Statistics Education, 2014
Bayesian methodology continues to be widely used in statistical applications. As a result, it is increasingly important to introduce students to Bayesian thinking at early stages in their mathematics and statistics education. While many students in upper level probability courses can recite the differences in the Frequentist and Bayesian…
Descriptors: Bayesian Statistics, Probability, College Mathematics, Mathematics Instruction
Benson, Eric – Journal of Instructional Pedagogies, 2013
The statistical output of interest to most elementary statistics students is the p-value, outputted in computer programs like SPSS, Minitab and SAS. Statistical decisions are sometimes made using these values without understanding the meaning or how these values are calculated. Most elementary statistics textbooks calculates p-values for z-tests…
Descriptors: Teaching Methods, Graphing Calculators, Statistics, Mathematics Instruction
Leemis, Lawrence M.; Luckett, Daniel J.; Powell, Austin G.; Vermeer, Peter E. – Journal of Statistics Education, 2012
We describe a web-based interactive graphic that can be used as a resource in introductory classes in mathematical statistics. This interactive graphic presents 76 common univariate distributions and gives details on (a) various features of the distribution such as the functional form of the probability density function and cumulative distribution…
Descriptors: Probability, Statistical Distributions, Transformations (Mathematics), Bayesian Statistics
International Journal of Mathematical Education in Science and Technology, 2007
In this issue's "Classroom Notes" section, the following papers are described: (1) "Sequences of Definite Integrals" by T. Dana-Picard; (2) "Structural Analysis of Pythagorean Monoids" by M.-Q Zhan and J. Tong; (3) "A Random Walk Phenomenon under an Interesting Stopping Rule" by S. Chakraborty; (4) "On Some Confidence Intervals for Estimating the…
Descriptors: Mathematics Education, Intervals, Least Squares Statistics, Equations (Mathematics)
Rahman, Mezbahur; Rahman, Rumanur; Pearson, Larry M. – International Journal of Mathematical Education in Science & Technology, 2006
Quantiles for finite mixtures of normal distributions are computed. The difference between a linear combination of independent normal random variables and a linear combination of independent normal densities is emphasized. (Contains 3 tables and 1 figure.)
Descriptors: Computation, Equations (Mathematics), Calculus, Statistical Distributions

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

Edgeman, Rick L. – Mathematics and Computer Education, 1988
Presents noncalculus approximation techniques for two normal distribution problems. These methods may be useful projects for lower-level undergraduate statistics and computer science students. (PK)
Descriptors: College Mathematics, Computer Assisted Instruction, Computer Science Education, Higher Education

Scheuermann, Larry – Journal of Computers in Mathematics and Science Teaching, 1989
Provides a short BASIC program, RANVAR, which generates random variates for various theoretical probability distributions. The seven variates include: uniform, exponential, normal, binomial, Poisson, Pascal, and triangular. (MVL)
Descriptors: College Mathematics, Computer Software, Computer Uses in Education, Courseware