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Direct linkVaske, 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
Download full textCrossley, Scott; McNamara, Danielle S.; Baker, Ryan; Wang, Yuan; Paquette, Luc; Barnes, Tiffany; Bergner, Yoav – International Educational Data Mining Society, 2015
Completion rates for massive open online classes (MOOCs) are notoriously low, but learner intent is an important factor. By studying students who drop out despite their intent to complete the MOOC, it may be possible to develop interventions to improve retention and learning outcomes. Previous research into predicting MOOC completion has focused…
Descriptors: Online Courses, Large Group Instruction, Information Retrieval, Data Analysis
Mavridis, Dimitris; Moustaki, Irini – Multivariate Behavioral Research, 2008
In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…
Descriptors: Simulation, Mathematics, Factor Analysis, Discriminant Analysis
Peer reviewedTate, Richard L. – Multivariate Behavioral Research, 1983
The use of generalized discriminant analysis as a descriptive technique which can be employed outside of the traditional analysis of variance studies is discussed. Examples based on real data are provided. (Author/JKS)
Descriptors: Data Analysis, Discriminant Analysis, Multivariate Analysis, Statistical Studies
Peer reviewedCohen, Jacob; Lee, Robert S. – Multivariate Behavioral Research, 1987
STATGRAPHICS, a statistical package written for the IBM PC/XT/AT, is reviewed. In addition to superb graphics, STATGRAPHICS is unequalled in time series procedures, quality control, linear programming, and other mathematical procedures. The modules for regression analysis, categorical data analysis, and nonparametric analysis are good, but contain…
Descriptors: Analysis of Variance, Cluster Analysis, Computer Graphics, Computer Software
