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David Voas; Laura Watt – Teaching Statistics: An International Journal for Teachers, 2025
Binary logistic regression is one of the most widely used statistical tools. The method uses odds, log odds, and odds ratios, which are difficult to understand and interpret. Understanding of logistic regression tends to fall down in one of three ways: (1) Many students and researchers come to believe that an odds ratio translates directly into…
Descriptors: Statistics, Statistics Education, Regression (Statistics), Misconceptions
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Iannario, Maria; Tarantola, Claudia – Sociological Methods & Research, 2023
This contribution deals with effect measures for covariates in ordinal data models to address the interpretation of the results on the extreme categories of the scales, evaluate possible response styles, and motivate collapsing of extreme categories. It provides a simpler interpretation of the influence of the covariates on the probability of the…
Descriptors: Data Analysis, Data Interpretation, Probability, Models
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Masnick, Amy M.; Morris, Bradley J. – Education Sciences, 2022
Data reasoning is an essential component of scientific reasoning, as a component of evidence evaluation. In this paper, we outline a model of scientific data reasoning that describes how data sensemaking underlies data reasoning. Data sensemaking, a relatively automatic process rooted in perceptual mechanisms that summarize large quantities of…
Descriptors: Models, Science Process Skills, Data Interpretation, Cognitive Processes
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Bradshaw, Laine; Levy, Roy – Educational Measurement: Issues and Practice, 2019
Although much research has been conducted on the psychometric properties of cognitive diagnostic models, they are only recently being used in operational settings to provide results to examinees and other stakeholders. Using this newer class of models in practice comes with a fresh challenge for diagnostic assessment developers: effectively…
Descriptors: Data Interpretation, Probability, Classification, Diagnostic Tests
López Puga, Jorge – Teaching Statistics: An International Journal for Teachers, 2014
The aprioristic (classical, naïve and symmetric) and frequentist interpretations of probability are commonly known. Bayesian or subjective interpretation of probability is receiving increasing attention. This paper describes an activity to help students differentiate between the three types of probability interpretations.
Descriptors: Probability, Bayesian Statistics, Data Interpretation, Instructional Materials
Porter, Kristin E.; Balu, Rekha – MDRC, 2016
Education systems are increasingly creating rich, longitudinal data sets with frequent, and even real-time, data updates of many student measures, including daily attendance, homework submissions, and exam scores. These data sets provide an opportunity for district and school staff members to move beyond an indicators-based approach and instead…
Descriptors: Models, Prediction, Statistical Analysis, Elementary Secondary Education
Letkowski, Jerzy – Journal of Case Studies in Education, 2014
Descripting Statistics provides methodology and tools for user-friendly presentation of random data. Among the summary measures that describe focal tendencies in random data, the mode is given the least amount of attention and it is frequently misinterpreted in many introductory textbooks on statistics. The purpose of the paper is to provide a…
Descriptors: Statistical Data, Data Interpretation, Statistics, Qualitative Research
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Drummond, Gordon B.; Vowler, Sarah L. – Advances in Physiology Education, 2011
Experimental data are analysed statistically to allow researchers to draw conclusions from a limited set of measurements. The hard fact is that researchers can never be certain that measurements from a sample will exactly reflect the properties of the entire group of possible candidates available to be studied (although using a sample is often the…
Descriptors: Educational Research, Statistical Inference, Data Interpretation, Probability
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Niculescu-Aron, Ileana Gabriela; Mihaescu, Constanta; Mazurencu Marinescu, Miruna; Asandului, Laura – Journal of Applied Quantitative Methods, 2006
We live in an era where IC&T generates numerous transformations to the classic way of learning. The most known results of these transformations concretise in two means of learning through IC&T: e-learning and computer assisted learning. Just like the classical ones, these models assume the existence of an efficient learning process based…
Descriptors: Student Attitudes, Computer Assisted Instruction, Electronic Learning, Information Technology
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Erosheva, Elena A. – Psychometrika, 2005
This paper focuses on model interpretation issues and employs a geometric approach to compare the potential value of using the Grade of Membership (GoM) model in representing population heterogeneity. We consider population heterogeneity manifolds generated by letting subject specific parameters vary over their natural range, while keeping other…
Descriptors: Mathematical Formulas, Research Methodology, Models, Comparative Analysis
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Hinders, Duane C. – Mathematics Teacher, 1990
Discusses the use or misuse of statistics or probability in society. Presented are examples from opinion polling, sports, the 1970 draft lottery, and the law. Lists 18 references. (YP)
Descriptors: Data Interpretation, Mathematical Applications, Mathematical Concepts, Mathematical Logic
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Barbella, Peter; And Others – Mathematics Teacher, 1990
Demonstrates a statistically valid method allowing students to explore randomization. Described are two examples: counting techniques for a small set of data and simulation for a large sample. (YP)
Descriptors: Data Analysis, Data Interpretation, Mathematical Concepts, Mathematical Logic
Shah, Chandra; Burke, Gerald – Centre for the Economics of Education and Training, Monash University, 2004
This report provides estimates of job and occupational mobility by demographic, educational and labour market variables using data from the Australian Bureau of Statistics (ABS) "Labour Mobility" survey for 2002. The report provides information on the effects of these variables on the probability of job separation. It also identifies the…
Descriptors: Labor Market, Education Work Relationship, Occupational Mobility, Probability