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Exploratory research is "the preliminary research to clarify the exact nature of the problem to be solved." It is used to ensure additional research is taken into consideration during an experiment as well as determining research priorities, collecting data and honing in on certain subjects which may be difficult to take note of without exploratory research.
There are many ways to classify research designs. Nonetheless, the list below offers a number of useful distinctions between possible research designs. A research design is an arrangement of conditions or collection. [5] Descriptive (e.g., case-study, naturalistic observation, survey) Correlational (e.g., case-control study, observational study)
In the field of public administration working hypotheses are used as a conceptual framework for exploratory, applied, empirical research. [28] [29] [30] Research projects that use working hypotheses use a deductive reasoning or logic of inquiry. [3] In other words, the problem and preliminary theory are developed ahead of time and tested using ...
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."
Exploratory Factor Analysis Model. In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships between measured variables. [1]
Several types of conceptual frameworks have been identified, [13] [14] [19] and line up with a research purpose in the following ways: Working hypothesis – exploration or exploratory research [20] Pillar questions – exploration or exploratory research; Descriptive categories – description or descriptive research; Practical ideal type ...
Causal analysis is the field of experimental design and statistical analysis pertaining to establishing cause and effect. [1] [2] Exploratory causal analysis (ECA), also known as data causality or causal discovery [3] is the use of statistical algorithms to infer associations in observed data sets that are potentially causal under strict assumptions.
Research papers from more than 55 disciplines Free & Subscription No Elsevier: HAL: Multidisciplinary: 760,000 (2,000,000 metadata) [14] An open-access database for French researchers. Organized into institution and domain portals. Free Yes CNRS's Centre pour la Communication Scientifique Directe (CCSD) RePEc: Research Papers in Economics [15 ...