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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." [3] Exploratory data ...
Pages in category "Exploratory data analysis" The following 13 pages are in this category, out of 13 total. This list may not reflect recent changes. ...
Data exploration is an approach similar to initial data analysis, whereby a data analyst uses visual exploration to understand what is in a dataset and the characteristics of the data, rather than through traditional data management systems. [1]
They include conducting exploratory, hypothesis-free research, which the authors note "...pervades many of the researcher DFs that we describe below in the later phases of the study." Other DFs listed in this paper include the creation of multiple manipulated independent variables and the measurement of additional variables that may be selected ...
The entire data collection period is significantly shortened, as all data can be collected and processed in little more than a month. [2] Interaction between the respondent and the questionnaire is more dynamic compared to e-mail or paper surveys. [16] Online surveys are also less intrusive, and they suffer less from social desirability effects ...
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.
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.
Ordination or gradient analysis, in multivariate analysis, is a method complementary to data clustering, and used mainly in exploratory data analysis (rather than in hypothesis testing). In contrast to cluster analysis, ordination orders quantities in a (usually lower-dimensional) latent space. In the ordination space, quantities that are near ...