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  2. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    A statistical model can be used or not, but primarily EDA is for seeing what the data can tell beyond the formal modeling and thereby contrasts with traditional hypothesis testing, in which a model is supposed to be selected before the data is seen. Exploratory data analysis has been promoted by John Tukey since 1970 to encourage statisticians ...

  3. Exploratory research - Wikipedia

    en.wikipedia.org/wiki/Exploratory_research

    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.

  4. Exploratory factor analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_factor_analysis

    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]

  5. Bayesian statistics - Wikipedia

    en.wikipedia.org/wiki/Bayesian_statistics

    Exploratory analysis of Bayesian models is an adaptation or extension of the exploratory data analysis approach to the needs and peculiarities of Bayesian modeling. In the words of Persi Diaconis: [16] Exploratory data analysis seeks to reveal structure, or simple descriptions in data. We look at numbers or graphs and try to find patterns.

  6. Exploratory causal analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_causal_analysis

    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.

  7. Research question - Wikipedia

    en.wikipedia.org/wiki/Research_question

    A research question is "a question that a research project sets out to answer". [1] 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.

  8. Factor analysis - Wikipedia

    en.wikipedia.org/wiki/Factor_analysis

    Use quantitative marketing research techniques (such as surveys) to collect data from a sample of potential customers concerning their ratings of all the product attributes. Input the data into a statistical program and run the factor analysis procedure. The computer will yield a set of underlying attributes (or factors).

  9. Research design - Wikipedia

    en.wikipedia.org/wiki/Research_design

    A research design typically outlines the theories and models underlying a project; the research question(s) of a project; a strategy for gathering data and information; and a strategy for producing answers from the data. [1] A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or ...