Reasoning With Statistics: How to Read Quantitative Statistics, 5th Ed. Boston: Wasworth.

All procedures for the numerical representation of empirical facts

A delineation of data networks and big information.

Quantitative research is a inquiry strategy that focuses on quantifying the collection and analysis of data.^[1] It is formed from a deductive arroyo where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies.^[one]

Associated with the natural, applied, formal, and social sciences this inquiry strategy promotes the objective empirical investigation of observable phenomena to test and understand relationships. This is done through a range of quantifying methods and techniques, reflecting on its broad utilization as a research strategy beyond differing bookish disciplines.^{[ii] [3] [4]}

The objective of quantitative research is to develop and utilise mathematical models, theories, and hypotheses pertaining to phenomena. The process of measurement is cardinal to quantitative research because it provides the central connection between empirical ascertainment and mathematical expression of quantitative relationships.

Quantitative data is any data that is in numerical form such as statistics, percentages, etc.^[four] The researcher analyses the data with the help of statistics and hopes the numbers volition yield an unbiased result that can be generalized to some larger population. Qualitative research, on the other hand, inquires securely into specific experiences, with the intention of describing and exploring significant through text, narrative, or visual-based data, by developing themes exclusive to that set of participants.^[5]

Quantitative research is widely used in psychology, economics, demography, sociology, marketing, community wellness, wellness & human development, gender studies, and political science; and less often 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 enquiry produces information but on the particular cases studied, and whatever more full general conclusions are just hypotheses. Quantitative methods tin be used to verify which of such hypotheses are truthful. A comprehensive assay 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.^[6]

Overview [edit]

Quantitative enquiry 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
• Drove of empirical data
• Modeling and analysis of data

Quantitative enquiry is often contrasted with qualitative enquiry, 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.^[7] Approaches to quantitative psychology were first modeled on quantitative approaches in the concrete sciences by Gustav Fechner in his work on psychophysics, which congenital on the work of Ernst Heinrich Weber. Although a distinction is usually drawn between qualitative and quantitative aspects of scientific investigation, it has been argued that the two get hand in hand. For example, based on assay of the history of science, Kuhn concludes that "large amounts of qualitative work accept ordinarily been prerequisite to fruitful quantification in the physical sciences".^[8] Qualitative research is ofttimes used to proceeds a general sense of phenomena and to form theories that can be tested using further quantitative inquiry. For case, in the social sciences qualitative inquiry methods are often used to gain better understanding of such things as intentionality (from the speech response of the researchee) and pregnant (why did this person/group say something and what did it mean to them?) (Kieron Yeoman).

Although quantitative investigation of the globe has existed since people get-go began to tape events or objects that had been counted, the modernistic idea of quantitative processes have their roots in Auguste Comte's positivist framework.^[9] Positivism emphasized the use of the scientific method through observation to empirically exam 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 beliefs could accelerate.

Quantitative methods are an integral component of the v angles of analysis fostered by the data percolation methodology,^[10] which as well includes qualitative methods, reviews of the literature (including scholarly), interviews with experts and calculator simulation, and which forms an extension of data triangulation.

Quantitative methods accept limitations. These studies practise not provide reasoning behind participants' responses, they often do not reach underrepresented populations, and they may span long periods in society to collect the data.^[11]

Use of statistics [edit]

Statistics is the nigh widely used co-operative of mathematics in quantitative research outside of the concrete sciences, and besides finds applications within the physical sciences, such equally in statistical mechanics. Statistical methods are used extensively within fields such every bit economics, social sciences and biological science. Quantitative research using statistical methods starts with the collection of data, based on the hypothesis or theory. Usually a big sample of data is collected – this would require verification, validation and recording before the analysis can have place. Software packages such as SPSS and R are typically used for this purpose. Causal relationships are studied by manipulating factors thought to influence the phenomena of interest while controlling other variables relevant to the experimental outcomes. In the field of health, for example, researchers might measure and study the relationship between dietary intake and measurable physiological furnishings such equally weight loss, controlling for other key variables such every bit do. Quantitatively based stance surveys are widely used in the media, with statistics such every bit the proportion of respondents in favor of a position commonly reported. In opinion surveys, respondents are asked a fix of structured questions and their responses are tabulated. In the field of climate science, researchers compile and compare statistics such as temperature or atmospheric concentrations of carbon dioxide.

Empirical relationships and associations are also frequently studied by using some class of general linear model, non-linear model, or past using factor analysis. A fundamental principle in quantitative research is that correlation does non imply causation, although some such as Clive Granger suggest that a series of correlations can imply a degree of causality. This principle follows from the fact that it is always possible a spurious human relationship exists for variables betwixt which covariance is plant in some degree. Associations may exist examined between any combination of continuous and chiselled variables using methods of statistics.

Measurement [edit]

Views regarding the role of measurement in quantitative research are somewhat divergent. Measurement is often regarded equally existence just a means past which observations are expressed numerically in order to investigate causal relations or associations. Even so, information technology has been argued that measurement often plays a more important role in quantitative inquiry.^[12] For example, Kuhn argued that within quantitative research, the results that are shown can evidence to exist strange. This is because accepting a theory based on results of quantitative data could prove to be a natural phenomenon. He argued that such abnormalities are interesting when washed during the process of obtaining information, as seen below:

When measurement departs from theory, it is likely to yield mere numbers, and their very neutrality makes them especially sterile equally a source of remedial suggestions. Merely numbers register the departure from theory with an authority and finesse that no qualitative technique can duplicate, and that departure is often enough to start a search (Kuhn, 1961, p. 180).

In classical physics, the theory and definitions which underpin measurement are generally deterministic in nature. In contrast, probabilistic measurement models known every bit the Rasch model and Item response theory models are more often than not employed in the social sciences. Psychometrics is the subject field concerned with the theory and technique for measuring social and psychological attributes and phenomena. This field is fundamental to much quantitative enquiry that is undertaken inside the social sciences.

Quantitative research may involve the use of proxies as stand-ins for other quantities that cannot exist directly measured. Tree-band width, for example, is considered a reliable proxy of ambience environmental conditions such as the warmth of growing seasons or corporeality of rainfall. Although scientists cannot directly measure out the temperature of past years, tree-band width and other climate proxies have been used to provide a semi-quantitative record of boilerplate temperature in the Northern Hemisphere back to 1000 A.D. When used in this way, the proxy record (tree ring width, say) only reconstructs a certain amount of the variance of the original record. The proxy may be calibrated (for example, during the catamenia of the instrumental record) to make up one's mind how much variation is captured, including whether both short and long term variation is revealed. In the example of tree-ring width, different species in dissimilar places may show more or less sensitivity to, say, rainfall or temperature: when reconstructing a temperature record there is considerable skill in selecting proxies that are well correlated with the desired variable.^[13]

Relationship with qualitative methods [edit]

In near physical and biological sciences, the utilise of either quantitative or qualitative methods is uncontroversial, and each is used when appropriate. In the social sciences, particularly in sociology, social anthropology and psychology, the apply of one or other blazon of method tin can be a matter of controversy and even ideology, with particular schools of idea within each subject favouring i type of method and pouring contemptuousness on to the other. The majority trend throughout the history of social scientific discipline, all the same, is to use eclectic approaches-by combining both methods. Qualitative methods might be used to understand the meaning of the conclusions produced by quantitative methods. Using quantitative methods, it is possible to give precise and testable expression to qualitative ideas. This combination of quantitative and qualitative data gathering is frequently referred to as mixed-methods research.^[xiv]

Examples [edit]

• Research that consists of the per centum amounts of all the elements that make up Earth's atmosphere.
• Survey that concludes that the average patient has to wait two hours in the waiting room of a certain physician before being selected.
• An experiment in which group x was given ii tablets of aspirin a solar day and group y was given ii tablets of a placebo a day where each participant is randomly assigned to 1 or other of the groups. The numerical factors such as two tablets, percent of elements and the time of waiting brand the situations and results quantitative.
• In finance, quantitative inquiry into the stock markets is used to develop models to price complex trades, and develop algorithms to exploit investment hypotheses, as seen in quantitative hedge funds and Trading Strategy Indices.^[15]

Come across besides [edit]

• Antipositivism
• Instance written report research
• Econometrics
• Falsifiability
• Market place research
• Positivism
• Qualitative research
• Quantitative marketing research
• Quantitative psychology
• Quantification (science)
• Observational study
• Sociological positivism
• Statistical survey
• Statistics

References [edit]

1. ^ ^{a b} Bryman, Alan (2012). Social enquiry methods (4th ed.). Oxford: Oxford University Press. ISBN978-0-nineteen-958805-three. OCLC 751832004.
2. ^ Babbie, Earl R. (2010). The practice of social research (twelfth ed.). Belmont, Calif: Wadsworth Cengage. ISBN978-0-495-59841-ane. OCLC 317075477.
3. ^ Muijs, Daniel. Doing quantitative enquiry in teaching with SPSS (2nd ed.). Los Angeles. ISBN978-i-84920-323-iv. OCLC 656776067.
4. ^ ^{a b} Given, Lisa Yard. (2008). The SAGE Encyclopedia of Qualitative Research Methods. Los Angeles: SAGE Publications. ISBN978-1-4129-4163-1.
5. ^ Corrine, Glesne (2011). Condign Qualitative Researchers: An Introduction (4th ed.). Boston: Pearson. ISBN978-0137047970. OCLC 464594493.
6. ^ Hunter, Laura; Leahey, Erin (2008). "Collaborative Research in Sociology: Trends and Contributing Factors". The American Sociologist. 39 (4): 290–306. doi:10.1007/s12108-008-9042-ane.
7. ^ Massachusetts Plant of Technology, MIT OpenCourseWare. 11.201 Gateway to the Profession of Planning, Fall 2010. p. 4.
8. ^ Kuhn, Thomas S. (1961). "The Part of Measurement in Modern Physical Science". Isis. 52 (ii): 161–193 (162). doi:10.1086/349468. JSTOR 228678.
9. ^ Kasim, R.; Alexander, K.; Hudson, J. (2010). A choice of research strategy for identifying customs-based action skill requirements in the procedure of delivering housing market place renewal. Research Institute for the Congenital and Human Environs, University of Salford, UK.
10. ^ Mesly, Olivier (2015). Creating Models in Psychological Research. The states: Springer Psychology: 126 pages. ISBN 978-3-319-15752-8
11. ^ Goertzen, Melissa J. (2017). "Introduction to Quantitative Research and Data". Library Engineering science Reports. 53 (4): 12–18. ISSN 0024-2586.
12. ^ Moballeghi, 1000. & Moghaddam, K.G. (2008). "How Do We Measure Use of Scientific Journals? A Note on Research Methodologies". Scientometrics. 76 (i): 125–133. doi:10.1007/s11192-007-1901-y.
13. ^ Briffa, Keith R.; Osborn, Timothy J.; Schweingruber, Fritz H.; Harris, Ian C.; Jones, Philip D.; Shiyatov, Stepan G.; Vaganov, Eugene A. (2001). "Low-frequency temperature variations from a northern tree ring density network" (PDF). Journal of Geophysical Research. 106 (D3): 2929–2941. Bibcode:2001JGR...106.2929B. doi:x.1029/2000JD900617.
14. ^ Diriwächter, R. & Valsiner, J. (January 2006) Qualitative Developmental Research Methods in Their Historical and Epistemological Contexts. FQS. Vol 7, No. 1, Art. eight
15. ^ A Simple Overview of Quantitative Analysis. Investopeda, January 2018

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Source: https://en.wikipedia.org/wiki/Quantitative_research

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