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Donegan, Sarah; Dias, Sofia; Tudur-Smith, Catrin; Marinho, Valeria; Welton, Nicky J. – Research Synthesis Methods, 2018
Background: Meta-regression results must be interpreted taking into account the range of covariate values of the contributing studies. Results based on interpolation or extrapolation may be unreliable. In network meta-regression (NMR) models, which include covariates in network meta-analyses, results are estimated using direct and indirect…
Descriptors: Graphs, Networks, Meta Analysis, Regression (Statistics)
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Schild, Anne H. E.; Voracek, Martin – Research Synthesis Methods, 2015
Research has shown that forest plots are a gold standard in the visualization of meta-analytic results. However, research on the general interpretation of forest plots and the role of researchers' meta-analysis experience and field of study is still unavailable. Additionally, the traditional display of effect sizes, confidence intervals, and…
Descriptors: Graphs, Visualization, Meta Analysis, Data Interpretation
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Lem, Stephanie; Onghena, Patrick; Verschaffel, Lieven; Van Dooren, Wim – Educational Psychology, 2013
Recent studies have shown that the interpretation of graphs is not always easy for students. In order to reason properly about distributions of data, however, one needs to be able to interpret graphical representations of these distributions correctly. In this study, we used Tversky's principles for the design of graphs to explain how 125…
Descriptors: Graphs, Data Interpretation, College Freshmen, Design
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Simsek, Omer; Yazar, Taha – Eurasian Journal of Educational Research, 2016
Problem Statement: The educational technology standards for teachers set by the International Society for Technology in Education (the ISTE Standards-T) represent an important framework for using technology effectively in teaching and learning processes. These standards are widely used by universities, educational institutions, and schools. The…
Descriptors: Educational Technology, Self Efficacy, Validity, Reliability
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Lem, Stephanie; Onghana, Patrick; Verschaffel, Lieven; Van Dooren, Wim – Statistics Education Research Journal, 2013
Data distributions can be represented using different external representations, such as histograms and boxplots. Although the role of external representations has been extensively studied in mathematics, this is less the case in statistics. This study helps to fill this gap by systematically varying the representation that accompanies a task…
Descriptors: Foreign Countries, Graphs, Statistical Distributions, College Freshmen
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Laumakis, Paul – Mathematics Teacher, 2011
When taking mathematics courses, students will sometimes ask their recurring question, "When will I ever use this in real life?" Educators are often unable to provide a direct connection between what they are teaching in the classroom and a real-life application. However, when such an opportunity does arise, they should seize it and…
Descriptors: Regression (Statistics), Mathematics Instruction, Mathematics, Mathematics Curriculum
Actuarial Foundation, 2012
The purpose of these modules is to provide an introduction to the world of probability and statistics to accelerated mathematics students at the high school level. The materials are centered on the fictional town of Happy Shores, a coastal community which is at risk for hurricanes. Actuaries at an insurance company figure out the risks and…
Descriptors: Mathematical Concepts, Probability, Statistics, Learning Modules
Hecht, Jeffrey B. – 1992
Previous research has demonstrated particular inadequacies in conventional methods used to identify outlier cases in bivariate regression models. Only through a combination of methods can one detect all of the deviant points potentially overinfluencing a regression model's parameters. This paper investigates whether a range of data points might…
Descriptors: Estimation (Mathematics), Graphs, Least Squares Statistics, Mathematical Models
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Barr, Aiala; Sichel, Herbert S. – Journal of the American Society for Information Science, 1991
Discussion of models for library circulation data highlights a new statistical prediction model that creates a flexible regression curve. Linear graphs that result from previous models are discussed, bivariate discrete distributions are explained, and graphs that show library circulation for one year at a time are presented. (nine references) (LRW)
Descriptors: Correlation, Data Analysis, Graphs, Library Circulation