Quantitative research
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What is it?
Quantitative approaches aim to test hypotheses, and usually to identify numerical differences between groups (i.e., quantities). The focus is on measurement, hypothesis-testing, explanation, and prediction. The goal (or claim) is objectivity.

Background/context and objectives
Quantitative research involves deductive reasoning, a top-down approach that works from the general to the specific. It considers a potential cause of something and hopes to verify its effect.

Elements/components
Creswell (2009) provides an excellent summary of the key elements of quantitative research: “Quantitative research is a means for testing objective theories by examining the relationship among variables. These variables, in turn can be measured, typically by instruments so that numbered data can be analyzed using statistical procedures. The final written report has a set structure consisting of introduction, literature and theory, methods, results and discussion...those who engage in this form of enquiry have assumptions about testing theories deductively, building in protections against bias, controlling for alternative explanations, and being able to generalize and replicate the findings.” [1]

Guidance for applying the framework
Quantitative research problems are formulated through a deductive logic; that is starting with a general construct or theory, then identifying some operational variables to quantify the general construct or theory, and finally deciding on which variables to be observed. Quantitative research design generally begins with the development of both a purpose and a problem statement, followed by the development of research questions.

A research problem statement is a clear, concise description of what a particular body of research (context) the study intends to focus on, which is generally an unknown that is worth investigating (significant and compelling). The problem statement is used to limit the scope of the problem, and highlights the potential for research results to advance knowledge and, when applied, contribute to practice. Quantitative research problems are formulated through a deductive logic, that is, starting with a general construct or theory, then identifying some operational variables to quantify the general construct or theory, and finally deciding on which variables to be observed.

A quantitative research purpose statement identifies the variables, and their relationships, the site for research, and when appropriate, the theory to be tested. This statement generally includes the independent variable (1st position in sentence), which influences or explains the dependent variable (2nd position in sentence), the control and/or mediating variable (3rd position in sentence), and the scope of the research (e.g., the research site, time frame, participants).

The research is then centered on clear, focused, concise (though potentially complex) and arguable questions. Quantitative research questions identify the variables under study, the population being studied and the testability of the question while also delimiting the research in space and time. Quantitative research questions tend to be more close, relating two or more variables and/or comparing two or more groups in order to understand probable cause and effect and/or differences in magnitude or frequency. They tend to begin with “how”, “what” or “why”, specify the independent, dependent, and mediating or control variables, and use words like “describe”, “compare” or “relate” to indicate the action or connection among the variables.

Good practice tips
Quantitative research methods are ideally employed after the pattern of something is understood well enough that these methods can help understand the variability in that pattern. If, for example, a survey is designed before the pattern has been clearly defined, there is a risk that the questions in the survey will miss what is important.

Success stories
Quantitative research methods have been used to help understand and contribute to helping solve society’s greatest challenges. Significant technological enhancements in data discoverability, interoperability, and analytics are making it possible to achieve research results that will cover a wide range of complex issues in the future. At a more local scale, quantitative research methods, particularly when employed with qualitative methods, can enrich understanding of social phenomena, decision making and behavior.

To learn more
[1] Creswell, J.D. 2009. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Sage, Thousand Oaks, California, USA, p.4.

Bernard, H.R. 2006. Research Methods in Anthropology: Qualitative and Quantitative Approaches. Altamira Press, Lanham, Maryland, USA.

Maxim, P.S. 1999. Quantitative Research Methods in the Social Sciences. Oxford University Press, New York, USA.

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Created on 27 Sep 2016 07:46 by Barron Orr
Updated on 11 Oct 2016 12:53 by Barron Orr

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