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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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Cho, Jaehee; Lee, H. Erin; Quinlan, Margaret – Journal of American College Health, 2017
Objective: Based on the technology acceptance model (TAM), we explored the nationally-bounded roles of four predictors (subjective norms, entertainment, recordability, and networkability) in determining the TAM variables of perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI) to use diet/fitness apps on…
Descriptors: Cross Cultural Studies, Telecommunications, Handheld Devices, College Students
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Paige, Samantha R.; Stellefson, Michael; Chaney, Beth H.; Chaney, Don J.; Alber, Julia M.; Chappell, Chelsea; Barry, Adam E. – American Journal of Health Education, 2017
Background: College students actively seek online health information and use Instagram, an image- and video-based social networking website, to build social networks grounded in trust and behavioral norms (social capital), which have the potential to prevent chronic disease. Purpose: This study aimed to (1) examine how intensity of Instagram use…
Descriptors: Correlation, Social Capital, Social Networks, Web Sites
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Chen, Ruey-Shin; Liu, I-Fan – Journal of Educational Computing Research, 2017
Currently, e-learning systems are being widely used in all stages of education. However, it is difficult for school administrators to accurately assess the actual usage performance of a new system, especially when an organization wishes to update the system for users from different backgrounds using new devices such as smartphones. To allow school…
Descriptors: Educational Technology, Technology Uses in Education, College Students, Student Attitudes
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Olinsky, Alan; Schumacher, Phyllis; Quinn, John – International Journal for Mathematics Teaching and Learning, 2012
In this paper, we discuss the importance of teaching power considerations in statistical hypothesis testing. Statistical power analysis determines the ability of a study to detect a meaningful effect size, where the effect size is the difference between the hypothesized value of the population parameter under the null hypothesis and the true value…
Descriptors: Testing, Sample Size, Hypothesis Testing, Statistics
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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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Rubin, Beth; Fernandes, Ron; Avgerinou, Maria D. – Internet and Higher Education, 2013
This paper extends the research on the Community of Inquiry (CoI) framework of understanding features of successful online learning to include the effects of the software used to support and facilitate it. This study examines how the Learning Management System (LMS) affords people the ability to take actions in an online course. A model is…
Descriptors: Educational Technology, Integrated Learning Systems, Electronic Learning, Distance Education
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van de Schoot, Rens; Hoijtink, Herbert; Dekovic, Maja – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Researchers often have expectations that can be expressed in the form of inequality constraints among the parameters of a structural equation model. It is currently not possible to test these so-called informative hypotheses in structural equation modeling software. We offer a solution to this problem using M"plus." The hypotheses are…
Descriptors: Structural Equation Models, Computer Software, Hypothesis Testing, Statistical Analysis
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LaFleur, Bonnie J.; Greevy, Robert A. – Journal of Clinical Child and Adolescent Psychology, 2009
A resampling-based method of inference--permutation tests--is often used when distributional assumptions are questionable or unmet. Not only are these methods useful for obvious departures from parametric assumptions (e.g., normality) and small sample sizes, but they are also more robust than their parametric counterparts in the presences of…
Descriptors: Sampling, Statistical Inference, Nonparametric Statistics, Hypothesis Testing
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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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Cai, Li; Hayes, Andrew F. – Journal of Educational and Behavioral Statistics, 2008
When the errors in an ordinary least squares (OLS) regression model are heteroscedastic, hypothesis tests involving the regression coefficients can have Type I error rates that are far from the nominal significance level. Asymptotically, this problem can be rectified with the use of a heteroscedasticity-consistent covariance matrix (HCCM)…
Descriptors: Least Squares Statistics, Error Patterns, Error Correction, Computation
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Morris, John D.; Huberty, Carl J. – Journal of Experimental Education, 1995
A method is presented for extending full versus restricted model testing to predictive discriminant analysis when the criterion of model accuracy is classification hit rate. An example is presented involving the dropout or school persistence of 76 5th graders, and a computer program for the analysis is introduced. (SLD)
Descriptors: Academic Persistence, Classification, Computer Software, Dropouts
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries