Document Type
Book Chapter
Publication Date
2017
Publication Title
The BERA/SAGE Handbook of Educational Research
Pages
19
Publisher Name
SAGE Publishing
Publisher Location
New York
Abstract
If you take theory and models seriously, then (a) you need to elaborate clearly for yourself ‘what counts’ and how things supposedly fit together, and (b) you must hold yourself accountable to data.… From my perspective, theory is – or should be – the lifeblood of the empirical scientist. (Schoenfeld, 2010, p. 105)
The process of theorizing, collecting evidence, testing theory, revising theory, and then working through the cycle again is the basis of science. Theory is no less important when conducting a data analysis using quantitative methods. All statistical textbooks spend significant space on discussing the assumptions of statistical tests, the data requirements for a given estimation procedure, and the boundaries around the conclusions that can be drawn from results. Theory about the phenomenon that one is examining through quantitative data analysis is not only the driver for the methods used to collect evidence, but most importantly, the decisions made about how to model and test that theory.
Identifier
9781473918917
Recommended Citation
Pigott, Terri D.. The Role of Theory in Quantitative Data Analysis. The BERA/SAGE Handbook of Educational Research, , : 19, 2017. Retrieved from Loyola eCommons, Education: School of Education Faculty Publications and Other Works,
Copyright Statement
© Terri D. Pigott 2017
Comments
Author Posting. © Terri D. Pigott 2017. This chapter is posted here by permission of SAGE Publishing for personal use, not for redistribution. The chapter was published in The BERA/SAGE Handbook of Educational Research, 2017, https://us.sagepub.com/en-us/nam/the-berasage-handbook-of-educational-research/book245556#description