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Zachary del Rosario – Journal of Statistics and Data Science Education, 2024
Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This study investigated the professional practices of working engineers to develop such a framework. The Neglected,…
Descriptors: Foreign Countries, Engineering Education, Engineering, Technical Occupations
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Karazsia, Bryan T.; Wong, Kendal – Teaching of Psychology, 2016
Quantitative and statistical literacy are core domains in the undergraduate psychology curriculum. An important component of such literacy includes interpretation of visual aids, such as tables containing results from statistical analyses. This article presents results of a quasi-experimental study with longitudinal follow-up that tested the…
Descriptors: Quasiexperimental Design, Followup Studies, Undergraduate Students, Visual Aids
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Sole, Marla A. – Mathematics Teacher, 2016
Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…
Descriptors: Statistics, Mathematics Instruction, Data Collection, Teaching Methods
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Ludlow, Larry; Klein, Kelsey – Journal of Statistics Education, 2014
Correlated predictors in regression models are a fact of life in applied social science research. The extent to which they are correlated will influence the estimates and statistics associated with the other variables they are modeled along with. These effects, for example, may include enhanced regression coefficients for the other variables--a…
Descriptors: Statistics, Correlation, Predictor Variables, Regression (Statistics)
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Raju, Dheeraj; Schumacker, Randall – Journal of College Student Retention: Research, Theory & Practice, 2015
The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…
Descriptors: Student Characteristics, Higher Education, Graduation Rate, Academic Persistence
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Hagedorn, Linda Serra; Cabrera, Alberto; Prather, George – Journal of College Student Retention: Research, Theory & Practice, 2011
Using a newly developed software application entitled "The Community College Transfer Calculator"[C], this article both quantifies the effect of specific course-taking patterns and stresses the need for an easy to understand tool for community college academic advisors, faculty, and students. The "Calculator" calculates the…
Descriptors: Community Colleges, Course Selection (Students), College Transfer Students, Computer Software
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Kee, Chang Peng; Osman, Kamisah; Ahmad, Fauziah – International Education Studies, 2013
Statistical analysis is one component that cannot be avoided in a quantitative research. Initial observations noted that students in higher education institution faced difficulty analysing quantitative data which were attributed to the confusions of various variable measurements. This paper aims to compare the outcomes of two approaches applied in…
Descriptors: Statistical Analysis, Teaching Methods, Instructional Effectiveness, Instructional Innovation
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Marks, Gary N. – School Effectiveness and School Improvement, 2010
The purpose of this paper is to identify school effects on student performance for tertiary entrance in Australia, taking into account student-level predictors using longitudinal data from the 2003 Programme for International Student Assessment (PISA) study. It finds that aspects of schooling, such as positive attitudes to school and disciplinary…
Descriptors: Academic Achievement, Foreign Countries, Longitudinal Studies, Performance Factors
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Wurtz, Keith – Journal of Applied Research in the Community College, 2008
The purpose of this article is to provide the necessary tools for institutional researchers to conduct a logistic regression analysis and interpret the results. Aspects of the logistic regression procedure that are necessary to evaluate models are presented and discussed with an emphasis on cutoff values and choosing the appropriate number of…
Descriptors: Regression (Statistics), Predictor Variables, Educational Background, Grades (Scholastic)