Provides examples of the use of computer simulation to help beginners develop a grasp for difficult statistical concepts. The implementation of this teaching methodology is discussed and analysis of simulation output through use of standard statistical software packages is illustrated. (Author/MBR)
Described is a Monte-Carlo method for modeling physical systems with a computer. Also discussed are ways to incorporate Monte-Carlo simulation techniques for introductory science and mathematics teaching and also for enriching computer and simulation courses. (RH)
Argues that the teaching of statistics can be freed from the tedium of routine and repetitive calculations with the use of several creative approaches. Concludes that these approaches enable students to invent and seek applications as a result of their own initiative and understanding. (MS)
Four activities are outlined that give students the opportunity to organize and display data. Selecting topics and various ways of displaying data with a microcomputer are discussed. (MNS)
Discusses the use of computers in teaching these courses at the Eindhoven University of Technology: (1) regression analysis; (2) generalized linear models; and (3) multivariate statistical methods. Students also use the computer for their final studies for validating statistical tests. (JN)
Proposes an alternative means of approximating the value of complex integrals, the Monte Carlo procedure. Incorporating a discrete approach and probability, an approximation is obtained from the ratio of computer-generated points falling under the curve to the number of points generated in a predetermined rectangle. (MDH)
Describes the use of programs written in BASIC and graphics facilities of microcomputers to make students aware of the assumptions of statistical models in linear regression and the design of experiments. Two references are cited. (CHC)
How the microcomputer can be used to reinforce basic statistical concepts and techniques is presented. The methods for achieving this include specific statistical problems, projects, games, and simulations for use with microcomputers. (MNS)
Examined individual differences in procedures for learning to use a statistical computing package among 36 students who were computer novices. Ss provided think aloud protocols over sessions of learning to use the package. Success in learning depended on use of particular learning procedures. In Exp 1, 5 faster learners tackled problems in a goal-directed, structured manner, abandoning one approach when appropriate and trying alternative approaches. The 5 slower learners engaged in unsystematic trial and error search, were repetitive in their approaches to problem solving, gave up more frequently, and paid less attention to prompts and error messages. In Exp 2, instructing Ss to use the effective procedures identified in Exp 1 enhanced their performance on statistical computing problems. (PsycLIT Database Copyright 1990 American Psychological Assn, all rights reserved)
This article investigates two common methods of determining the line of best fit and then expands on the techniques used in these methods to find the line of best fit by graphing, estimating and using a microcomputer. (PK)