Descriptor
Computer Software | 5 |
Estimation (Mathematics) | 5 |
Monte Carlo Methods | 5 |
Research Methodology | 2 |
Sampling | 2 |
Structural Equation Models | 2 |
Bayesian Statistics | 1 |
Chi Square | 1 |
College Mathematics | 1 |
Comparative Analysis | 1 |
Computer Interfaces | 1 |
More ▼ |
Author
Chin, Wynne W. | 1 |
Hancock, Gregory R. | 1 |
Harwell, Michael R. | 1 |
MacFarlane, J. D. | 1 |
Mittag, Kathleen Cage | 1 |
Nevitt, Johnathan | 1 |
Newell, G. J. | 1 |
Publication Type
Journal Articles | 3 |
Reports - Evaluative | 3 |
Speeches/Meeting Papers | 2 |
Book/Product Reviews | 1 |
Reports - Descriptive | 1 |
Education Level
Audience
Practitioners | 1 |
Teachers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating

Chin, Wynne W. – Structural Equation Modeling, 1996
The SEPATH structural equation modeling (SEM) software is a new module in the latest release of STATISTICA (version 5.0) for Windows 3.1 and Windows 95. SEPATH is a program that provides a comprehensive set of functions for the SEM modeling. The interface and the Monte Carlo capability are strong features. (SLD)
Descriptors: Computer Interfaces, Computer Software, Data Analysis, Estimation (Mathematics)

Harwell, Michael R. – Educational and Psychological Measurement, 1997
Results from two Monte Carlo studies in item response theory (comparisons of computer item analysis programs and Bayes estimation procedures) are analyzed with inferential methods to illustrate the procedures' strengths. It is recommended that researchers in item response theory use both descriptive and inferential methods to analyze Monte Carlo…
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Software, Estimation (Mathematics)
Nevitt, Johnathan; Hancock, Gregory R. – 1998
Though common structural equation modeling (SEM) methods are predicated upon the assumption of multivariate normality, applied researchers often find themselves with data clearly violating this assumption and without sufficient sample size to use distribution-free estimation methods. Fortunately, promising alternatives are being integrated into…
Descriptors: Chi Square, Computer Software, Error of Measurement, Estimation (Mathematics)

Newell, G. J.; MacFarlane, J. D. – Australian Mathematics Teacher, 1985
Presents sports-oriented examples (cricket and football) in which Monte Carlo methods are used on microcomputers to teach probability concepts. Both examples include computer programs (with listings) which utilize the microcomputer's random number generator. Instructional strategies, with further challenges to help students understand the role of…
Descriptors: Computer Simulation, Computer Software, Estimation (Mathematics), Mathematics Education
Correcting for Systematic Bias in Sample Estimates of Population Variances: Why Do We Divide by n-1?

Mittag, Kathleen Cage – 1992
An important topic presented in introductory statistics courses is the estimation of population parameters using samples. Students learn that when estimating population variances using sample data, we always get an underestimate of the population variance if we divide by n rather than n-1. One implication of this correction is that the degree of…
Descriptors: College Mathematics, Computer Software, Equations (Mathematics), Estimation (Mathematics)