Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 7 |
Descriptor
Source
Author
Publication Type
| Reports - Research | 78 |
| Journal Articles | 31 |
| Speeches/Meeting Papers | 13 |
| Information Analyses | 1 |
| Numerical/Quantitative Data | 1 |
| Opinion Papers | 1 |
Education Level
| Elementary Education | 3 |
| Higher Education | 2 |
| Middle Schools | 2 |
| Postsecondary Education | 2 |
| Secondary Education | 2 |
| Elementary Secondary Education | 1 |
| Grade 6 | 1 |
| Grade 8 | 1 |
| Intermediate Grades | 1 |
| Junior High Schools | 1 |
Audience
| Researchers | 8 |
Laws, Policies, & Programs
| Elementary and Secondary… | 2 |
Assessments and Surveys
| Armed Services Vocational… | 2 |
| National Longitudinal Study… | 2 |
| Advanced Placement… | 1 |
| General Educational… | 1 |
| National Assessment of… | 1 |
| SAT (College Admission Test) | 1 |
| Trends in International… | 1 |
What Works Clearinghouse Rating
Aridor, Keren; Ben-Zvi, Dani – ZDM: The International Journal on Mathematics Education, 2018
While aggregate reasoning is a core aspect of statistical reasoning, its development is a key challenge in statistics education. In this study we examine how students' aggregate reasoning with samples and sampling (ARWSS) can emerge in the context of statistical modeling activities of real phenomena. We present a case study on the emergent ARWSS…
Descriptors: Grade 6, Student Attitudes, Thinking Skills, Statistics
Braham, Hana Manor; Ben-Zvi, Dani – Statistics Education Research Journal, 2017
A fundamental aspect of statistical inference is representation of real-world data using statistical models. This article analyzes students' articulations of statistical models and modeling during their first steps in making informal statistical inferences. An integrated modeling approach (IMA) was designed and implemented to help students…
Descriptors: Foreign Countries, Elementary School Students, Statistical Inference, Mathematical Models
Çelik, H. Coskun – Educational Research and Reviews, 2017
The aim of the present study was to examine the mathematical modelling studies done between 2004 and 2015 in Turkey and to reveal their tendencies. Forty-nine studies were selected using purposeful sampling based on the term, "mathematical modelling" with Higher Education Academic Search Engine. They were analyzed with content analysis.…
Descriptors: Mathematical Models, Foreign Countries, Content Analysis, Qualitative Research
Tipton, Elizabeth; Pustejovsky, James E. – Society for Research on Educational Effectiveness, 2015
Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…
Descriptors: Randomized Controlled Trials, Sample Size, Effect Size, Hypothesis Testing
Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
Bentler, Peter M.; Satorra, Albert – Psychological Methods, 2010
When using existing technology, it can be hard or impossible to determine whether two structural equation models that are being considered may be nested. There is also no routine technology for evaluating whether two very different structural models may be equivalent. A simple nesting and equivalence testing (NET) procedure is proposed that uses…
Descriptors: Structural Equation Models, Testing, Simulation, Sampling
Ray, Darrell L. – American Biology Teacher, 2013
Students often enter biology programs deficient in the math and computational skills that would enhance their attainment of a deeper understanding of the discipline. To address some of these concerns, I developed a series of spreadsheet simulation exercises that focus on some of the mathematical foundations of scientific inquiry and the benefits…
Descriptors: Science Instruction, Mathematics Skills, Educational Technology, Spreadsheets
Luh, Wei-Ming; Olejnik, Stephen – 1990
Two-stage sampling procedures for comparing two population means when variances are heterogeneous have been developed by D. G. Chapman (1950) and B. K. Ghosh (1975). Both procedures assume sampling from populations that are normally distributed. The present study reports on the effect that sampling from non-normal distributions has on Type I error…
Descriptors: Comparative Analysis, Mathematical Models, Power (Statistics), Sample Size
Thissen, David; Wainer, Howard – 1983
A statistical method is described and illustrated which provides confidence envelopes around item response functions. Examples of 95 percent confidence envelopes for the one-, two-, and three-parameter logistic response models are given. In addition, the authors describe N-line plots, which show the genesis of the envelope as well as the density…
Descriptors: Graphs, Latent Trait Theory, Mathematical Formulas, Mathematical Models
Kalsbeek, William D.; And Others – 1975
The National Assessment of Educational Progress; Second Science Assessment No-Show Study assessed the magnitude and causation of nonresponse biases. A No-Show is defined as an individual who was selected as a sample respondent but failed to be present for regular assessment of the 17-year-old group. The procedure whereby a sample of eligible…
Descriptors: Educational Assessment, High Schools, Mathematical Models, Performance Factors
Peer reviewedVelicer, Wayne F.; Fava, Joseph L. – Multivariate Behavioral Research, 1987
Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…
Descriptors: Analysis of Variance, Factor Analysis, Mathematical Models, Matrices
Ary, Donald; Karabinus, Robert – 1975
The power of a statistical test is, in part, a function of the reliability of the dependable variable being analyzed. The substitution of sigma square divided by the reliability coefficient for sigma is proposed. This enables the researcher to incorporate dependent variable reliability information when determining the sample size required for a…
Descriptors: Hypothesis Testing, Mathematical Models, Measurement Techniques, Reliability
Peer reviewedPenfield, Douglas A.; Koffler, Stephen L. – Educational and Psychological Measurement, 1986
The development of a nonparametric K-sample test for equality of slopes using Puri's generalized L statistic is presented. The test is recommended when the assumptions underlying the parametric model are violated. This procedure replaces original data with either ranks (for data with heavy tails) or normal scores (for data with light tails).…
Descriptors: Mathematical Models, Nonparametric Statistics, Regression (Statistics), Sampling
The Maximal Value of a Zipf Size Variable: Sampling Properties and Relationship to Other Parameters.
Peer reviewedTague, Jean; Nicholls, Paul – Information Processing and Management, 1987
Examines relationships among the parameters of the Zipf size-frequency distribution as well as its sampling properties. Highlights include its importance in bibliometrics, tables for the sampling distribution of the maximal value of a finite Zipf distribution, and an approximation formula for confidence intervals. (Author/LRW)
Descriptors: Bibliometrics, Least Squares Statistics, Mathematical Models, Research Methodology
Peer reviewedMuthen, Bengt; Joreskog, Karl G. – Evaluation Review, 1983
Selectivity problems are discussed in terms of a general model that is estimated by the maximum likelihood method. Both single-group and multiple-group analyses are considered. An extension of the general model to latent variable models is discussed. (Author/PN)
Descriptors: Mathematical Models, Maximum Likelihood Statistics, Quasiexperimental Design, Research Methodology

Direct link
