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Showing 1 to 15 of 28 results Save | Export
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Carlos Cinelli; Andrew Forney; Judea Pearl – Sociological Methods & Research, 2024
Many students of statistics and econometrics express frustration with the way a problem known as "bad control" is treated in the traditional literature. The issue arises when the addition of a variable to a regression equation produces an unintended discrepancy between the regression coefficient and the effect that the coefficient is…
Descriptors: Regression (Statistics), Robustness (Statistics), Error of Measurement, Testing Problems
Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
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Wagaman, John C. – Teaching Statistics: An International Journal for Teachers, 2017
This article describes four semesters of introductory statistics courses that incorporate service learning and gardening into the curriculum with applications of the binomial distribution, least squares regression and hypothesis testing. The activities span multiple semesters and are iterative in nature.
Descriptors: Introductory Courses, Statistics, Service Learning, Gardening
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Jarosz, Andrew F.; Wiley, Jennifer – Journal of Problem Solving, 2014
The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the "Journal of Problem Solving." The Bayes factor provides information with a similar purpose to the "p"-value--to allow the researcher to make…
Descriptors: Problem Solving, Bayesian Statistics, Statistical Inference, Computation
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Lazarova, Krassi – Journal of College Science Teaching, 2015
Studying physics for nonphysics majors at college level is usually a process of learning new problem-solving skills and sometimes seems a frustrating experience. In an attempt to provide students with more learning resources, online homework was required to supplement the instruction. This study reveals the role of the online homework assignments…
Descriptors: Electronic Learning, Homework, Introductory Courses, Physics
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Curran-Everett, Douglas – Advances in Physiology Education, 2011
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This seventh installment of "Explorations in Statistics" explores regression, a technique that estimates the nature of the relationship between two things for which we may only surmise a mechanistic or predictive…
Descriptors: Regression (Statistics), Statistics, Models, Correlation
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Chen, Fang; Chalhoub-Deville, Micheline – Language Testing, 2014
Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…
Descriptors: Regression (Statistics), Language Tests, Language Proficiency, Mathematics Achievement
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Lovett, Steve; Johnson, Jennie – Journal of the Scholarship of Teaching and Learning, 2012
The measurement of student learning is becoming increasingly important in U.S. higher education. One way to measure learning is through longitudinal testing, but this becomes especially difficult when applied to cumulative learning within programs in situations of low persistence. In particular, many Hispanic Serving Institutions (HSIs) find…
Descriptors: Testing, Student Evaluation, Evaluation Methods, Measurement Techniques
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Watkins, Joseph C. – CBE - Life Sciences Education, 2010
The choice of pedagogy in statistics should take advantage of the quantitative capabilities and scientific background of the students. In this article, we propose a model for a statistics course that assumes student competency in calculus and a broadening knowledge in biology. We illustrate our methods and practices through examples from the…
Descriptors: College Students, Biological Sciences, Statistics, Calculus
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Wilson, Mark; Moore, Stephen – Language Testing, 2011
This paper provides a summary of a novel and integrated way to think about the item response models (most often used in measurement applications in social science areas such as psychology, education, and especially testing of various kinds) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. In addition,…
Descriptors: Reading Comprehension, Testing, Social Sciences, Item Response Theory
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Eisenhauer, Joseph G. – Teaching Statistics: An International Journal for Teachers, 2009
Very little explanatory power is required in order for regressions to exhibit statistical significance. This article discusses some of the causes and implications. (Contains 2 tables.)
Descriptors: Statistical Significance, Educational Research, Sample Size, Probability
Castellano, Katherine E.; Ho, Andrew D. – Council of Chief State School Officers, 2013
This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…
Descriptors: Guides, Models, Academic Achievement, Achievement Gains
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DiStefano, Christine; Zhu, Min; Mindrila, Diana – Practical Assessment, Research & Evaluation, 2009
Following an exploratory factor analysis, factor scores may be computed and used in subsequent analyses. Factor scores are composite variables which provide information about an individual's placement on the factor(s). This article discusses popular methods to create factor scores under two different classes: refined and non-refined. Strengths and…
Descriptors: Factor Structure, Factor Analysis, Researchers, Scores
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Gordon, Sheldon P.; Gordon, Florence S. – PRIMUS, 2009
The authors describe a collection of dynamic interactive simulations for teaching and learning most of the important ideas and techniques of introductory statistics and probability. The modules cover such topics as randomness, simulations of probability experiments such as coin flipping, dice rolling and general binomial experiments, a simulation…
Descriptors: Intervals, Hypothesis Testing, Statistics, Probability
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Yan, Duanli; Lewis, Charles; Stocking, Martha – Journal of Educational and Behavioral Statistics, 2004
It is unrealistic to suppose that standard item response theory (IRT) models will be appropriate for all the new and currently considered computer-based tests. In addition to developing new models, we also need to give attention to the possibility of constructing and analyzing new tests without the aid of strong models. Computerized adaptive…
Descriptors: Nonparametric Statistics, Regression (Statistics), Adaptive Testing, Computer Assisted Testing
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