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  2. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    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 ...

  3. Category:Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Category:Exploratory_data...

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  4. John Tukey - Wikipedia

    en.wikipedia.org/wiki/John_Tukey

    Tukey emphasized the importance of having a more flexible attitude towards data analysis and of exploring data carefully to see what structures and information might be contained therein. He called this "exploratory data analysis" (EDA). In many ways, EDA was a precursor to data science. Tukey also realized the importance of computer science to ...

  5. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  6. List of EDA companies - Wikipedia

    en.wikipedia.org/wiki/List_of_EDA_companies

    Silicon Insight - Interactive program that works with 3rd party testers for controlling and logging of data on the device for at-speed testing; Yield Insight - Yield analysis program which looks at foundry and performance data to diagnose possible problems; HDL Designer Series; Through Solido Design Automation Acquisition

  7. 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.

  8. 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]

  9. Electronic design automation - Wikipedia

    en.wikipedia.org/wiki/Electronic_design_automation

    Within a few years, there were many companies specializing in EDA, each with a slightly different emphasis. The first trade show for EDA was held at the Design Automation Conference in 1984 and in 1986, Verilog, another popular high-level design language, was first introduced as a hardware description language by Gateway Design Automation ...