Quantitative research

In natural and social sciences, and sometimes in other fields, quantitative research is the systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques.[1] The objective of quantitative research is to develop and employ mathematical models, theories, and hypotheses pertaining to phenomena. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships.

Quantitative data is any data that is in numerical form such as statistics, percentages, etc.[1] The researcher analyses the data with the help of statistics and hopes the numbers will yield an unbiased result that can be generalized to some larger population. Qualitative research, on the other hand, inquires deeply into specific experiences, with the intention of describing and exploring meaning through text, narrative, or visual-based data, by developing themes exclusive to that set of participants.[2]

Quantitative research is widely used in psychology, economics, demography, sociology, marketing, community health, health & human development, gender studies, and political science; and less frequently in anthropology and history. Research in mathematical sciences, such as physics, is also "quantitative" by definition, though this use of the term differs in context. In the social sciences, the term relates to empirical methods originating in both philosophical positivism and the history of statistics, in contrast with qualitative research methods.

Qualitative research produces information only on the particular cases studied, and any more general conclusions are only hypotheses. Quantitative methods can be used to verify which of such hypotheses are true. A comprehensive analysis of 1274 articles published in the top two American sociology journals between 1935 and 2005 found that roughly two thirds of these articles used quantitative method.[3]

Overview

Quantitative research is generally closely affiliated with ideas from 'the scientific method', which can include:

  • The generation of models, theories and hypotheses
  • The development of instruments and methods for measurement
  • Experimental control and manipulation of variables
  • Collection of empirical data
  • Modeling and analysis of data

Quantitative research is often contrasted with qualitative research, which purports to be focused more on discovering underlying meanings and patterns of relationships, including classifications of types of phenomena and entities, in a manner that does not involve mathematical models.[4] Approaches to quantitative psychology were first modeled on quantitative approaches in the physical sciences by Gustav Fechner in his work on psychophysics, which built on the work of Ernst Heinrich Weber. Although a distinction is commonly drawn between qualitative and quantitative aspects of scientific investigation, it has been argued that the two go hand in hand. For example, based on analysis of the history of science, Kuhn concludes that “large amounts of qualitative work have usually been prerequisite to fruitful quantification in the physical sciences”.[5] Qualitative research is often used to gain a general sense of phenomena and to form theories that can be tested using further quantitative research. For instance, in the social sciences qualitative research methods are often used to gain better understanding of such things as intentionality (from the speech response of the researchee) and meaning (why did this person/group say something and what did it mean to them?) (Kieron Yeoman).

Although quantitative investigation of the world has existed since people first began to record events or objects that had been counted, the modern idea of quantitative processes have their roots in Auguste Comte's positivist framework.[6] Positivism emphasized the use of the scientific method through observation to empirically test hypotheses explaining and predicting what, where, why, how, and when phenomena occurred. Positivist scholars like Comte believed only scientific methods rather than previous spiritual explanations for human behavior could advance.

Quantitative methods are an integral component of the five angles of analysis fostered by the data percolation methodology,[7] which also includes qualitative methods, reviews of the literature (including scholarly), interviews with experts and computer simulation, and which forms an extension of data triangulation.

Quantitative methods have limitations. These studies do not provide reasoning behind participants' responses, they often do not reach underrepresented populations, and they may span long periods in order to collect the data.[8]