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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. [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 ...
Multiple factor analysis (MFA) is a factorial method [1] devoted to the study of tables in which a group of individuals is described by a set of variables (quantitative and / or qualitative) structured in groups.
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
Quantitative analysis also takes a deductive approach. [8] Examples of content-analytical variables and constructs can be found, for example, in the open-access database DOCA. This database compiles, systematizes, and evaluates relevant content-analytical variables of communication and political science research areas and topics.
Bibliometrics is the application of statistical methods to the study of bibliographic data, especially in scientific and library and information science contexts, and is closely associated with scientometrics (the analysis of scientific metrics and indicators) to the point that both fields largely overlap.
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."
Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation). [4]