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Quantitative research methods in chaos and complexity: from probability to post hoc regression analyses
Gilstrap, Donald L.
Gilstrap, Donald L.
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Gilstrap_2013b.pdf
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2013
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Article
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Keywords
Studies,Quantitative research methods,Complexity,Chaos and complexity theories,Education,Post hoc regression analysis
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Citation
Gilstrap, Donald L. 2013. Quantitative research methods in chaos and complexity: from probability to post hoc regression analyses. -- Complicity: Journal of Complexity and Education;v.10 no.1/2: pp.57-70
Abstract
In addition to qualitative methods presented in chaos and complexity theories in educational
research, this article addresses quantitative methods that may show potential for future research
studies. Although much in the social and behavioral sciences literature has focused on computer
simulations, this article explores current chaos and complexity methods that have the potential to
bridge the divide between qualitative and quantitative, as well as theoretical and applied, human
research studies. These methods include multiple linear regression, nonlinear regression,
stochastics, Monte Carlo methods, Markov Chains, and Lyapunov exponents. A postulate for post
hoc regression analysis is then presented as an example of an emergent, recursive, and iterative
quantitative method when dealing with interaction effects and collinearity among variables. This
postulate also highlights the power of both qualitative and quantitative chaos and complexity
theories in order to observe and describe both the micro and macro levels of systemic emergence.
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© Copyright 2013. The author, DONALD GILSTRAP, assigns to the University of Alberta and other educational and non-profit
institutions a non-exclusive license to use this document for personal use and in courses of instruction provided that the article is used
in full and this copyright statement is reproduced. The author also grant a non-exclusive license to the University of Alberta to
publish this document in full on the World Wide Web, and for the document to be published on mirrors on the World Wide Web. Any
other usage is prohibited without the express permission of the authors.
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University of Alberta
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Complicity: Journal of Complexity and Education;v.10 no.1/2
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1710-5668