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Lohr, Sharon; Schochet, Peter Z.; Sanders, Elizabeth – National Center for Education Research, 2014
Suppose an education researcher wants to test the impact of a high school drop-out prevention intervention in which at-risk students attend classes to receive intensive summer school instruction. The district will allow the researcher to randomly assign students to the treatment classes or to the control group. Half of the students (the treatment…
Descriptors: Educational Research, Research Design, Data Analysis, Intervention
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Buri, Olga Elizabeth Minchala; Stefos, Efstathios – International Education Studies, 2017
The objective of this study is to examine the social profile of students who are enrolled in Basic General Education in Ecuador. Both a descriptive and multidimensional statistical analysis was carried out based on the data provided by the National Survey of Employment, Unemployment and Underemployment in 2015. The descriptive analysis shows the…
Descriptors: Foreign Countries, Profiles, Data Analysis, General Education
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Chen, Yu-Hui; Rorissa, Abebe; Germain, Carol Anne – portal: Libraries and the Academy, 2015
The authors compared Web usability definitions, collected from library professionals at academic institutions of the Association of Research Libraries (ARL) through online surveys in 2007 and 2012, to determine whether library practitioners' perspectives had altered as information technologies evolved during this time. The authors applied three…
Descriptors: Definitions, Usability, Academic Libraries, Online Surveys
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Hubert, Lawrence; Baker, Frank B. – Journal of Educational Statistics, 1976
Presents an exposition of two data reduction methods--single-link and complete-link hierarchical clustering. Emphasis is on statistical techniques for evaluating the adequacy of a completed partition hierarchy and the individual partitions within the sequence. A numerical reanalysis of data illustrates the methodology. (RC)
Descriptors: Cluster Grouping, Data Analysis, Evaluation, Hypothesis Testing
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Peay, Edmund R. – Psychometrika, 1975
A class of closely related hierarchical grouping methods are discussed and a procedure which implements them in an integrated fashion is presented. These methods avoid some theoretical anomalies inherent in clustering and provide a framework for viewing partitioning and nonpartitioning grouping. Significant relationships between these methods and…
Descriptors: Classification, Cluster Grouping, Computer Programs, Data Analysis
Stanley, Julian C.; Livingston, Samuel A. – 1971
Besides the ubiquitous Pearson product-moment r, there are a number of other measures of relationship that are attenuated by errors of measurement and for which the relationship between true measures can be estimated. Among these are the correlation ratio (eta squared), Kelley's unbiased correlation ratio (epsilon squared), Hays' omega squared,…
Descriptors: Analysis of Variance, Cluster Grouping, Correlation, Data Analysis
Shafto, Michael – 1972
The purpose of this paper is to suggest a technique of cluster analysis which is similar in aim to the Interactive Intercolumnar Correlation Analysis (IICA), though different in detail. Two methods are proposed for extracting a single bipolar factor (a "contrast compenent") directly from the initial similarities matrix. The advantages of this…
Descriptors: Bibliographies, Classification, Cluster Analysis, Cluster Grouping
McRae, Douglas J. – 1971
Procedures for grouping students into homogeneous subsets have long interested educational researchers. The research reported in this paper is an investigation of a set of objective grouping procedures based on multivariate analysis considerations. Four multivariate functions that might serve as criteria for adequate grouping are given and…
Descriptors: Ability Grouping, Algorithms, Cluster Grouping, Criterion Referenced Tests