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Scholtz, Brenda; Calitz, Andre; Haupt, Ross – International Journal of Sustainability in Higher Education, 2018
Purpose: Higher education institutions (HEIs) face a number of challenges in effectively managing and reporting on sustainability information, such as siloes of data and a limited distribution of information. Business intelligence (BI) can assist in addressing the challenges faced by organisations. The purpose of this study was to propose a BI…
Descriptors: Business, Intelligence, Higher Education, Information Management
Lane, Forrest C.; Henson, Robin K. – Online Submission, 2010
Education research rarely lends itself to large scale experimental research and true randomization, leaving the researcher to quasi-experimental designs. The problem with quasi-experimental research is that underlying factors may impact group selection and lead to potentially biased results. One way to minimize the impact of non-randomization is…
Descriptors: Quasiexperimental Design, Research Methodology, Educational Research, Scores
Woldbeck, Tanya – 1998
This paper outlines two types of discriminant analysis, predictive discriminant analysis (PDA) and descriptive discriminant analysis (DDA). Important differences between PDA and DDA are introduced and discussed using a heuristic data set, specifically indicating the portions of the Statistical Package for the Social Sciences (SPSS) output relevant…
Descriptors: Computer Software, Discriminant Analysis, Heuristics, Mathematical Models
Fan, Xitao – 2001
Bootstrap analysis, both for nonparametric statistical inference and for describing sample results stability and replicability, has been gaining prominence among quantitative researchers in educational and psychological research. Procedurally, however, it is often quite a challenge for quantitative researchers to implement bootstrap analysis in…
Descriptors: Computer Software, Educational Research, Heuristics, Nonparametric Statistics