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Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data. [1] It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies.
The quantitative research designs are experimental, correlational, and survey (or descriptive). [41] Statistics derived from quantitative research can be used to establish the existence of associative or causal relationships between variables. Quantitative research is linked with the philosophical and theoretical stance of positivism.
Regardless of the field of or preference for defining data (quantitative or qualitative), accurate data collection is essential to maintain research integrity. The selection of appropriate data collection instruments (existing, modified, or newly developed) and delineated instructions for their correct use reduce the likelihood of errors .
Some measure of the undisputed general importance of quantification in the natural sciences can be gleaned from the following comments: "these are mere facts, but they are quantitative facts and the basis of science." [1] It seems to be held as universally true that "the foundation of quantification is measurement." [2]
The most important distinction between the initial data analysis phase and the main analysis phase, is that during initial data analysis one refrains from any analysis that is aimed at answering the original research question. [109] The initial data analysis phase is guided by the following four questions: [110]
Quantitative research is the main methodology of the natural sciences. ... Important advantages of quantitative methods include precision and reliability. However ...
Choosing a research question is an essential element of both quantitative and qualitative research. Investigation will require data collection and analysis, and the methodology for this will vary widely. Good research questions seek to improve knowledge on an important topic, and are usually narrow and specific. [1]
For quantitative analysis, data is coded usually into measured and recorded as nominal or ordinal variables.. Questionnaire data can be pre-coded (process of assigning codes to expected answers on designed questionnaire), field-coded (process of assigning codes as soon as data is available, usually during fieldwork), post-coded (coding of open questions on completed questionnaires) or office ...