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  2. StudyTube - Wikipedia

    en.wikipedia.org/wiki/StudyTube

    StudyTube, sometimes referred to as EduTube, is an informal group of content creators on YouTube whose content focuses on studying, test and exam preparation, and school. These types of YouTubers are known as StudyTubers.

  3. 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."

  4. Trend analysis - Wikipedia

    en.wikipedia.org/wiki/Trend_analysis

    If the trend can be assumed to be linear, trend analysis can be undertaken within a formal regression analysis, as described in Trend estimation. If the trends have other shapes than linear, trend testing can be done by non-parametric methods, e.g. Mann-Kendall test, which is a version of Kendall rank correlation coefficient.

  5. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]

  6. Gartner hype cycle - Wikipedia

    en.wikipedia.org/wiki/Gartner_hype_cycle

    Specific disadvantages when compared to, for example, technology readiness level are: The cycle is not scientific in nature, and there is no data or analysis that would justify the cycle. With the (subjective) terms disillusionment, enlightenment and expectations it cannot be described objectively or clearly where technology now really is.

  7. Analytics - Wikipedia

    en.wikipedia.org/wiki/Analytics

    Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.

  8. An overhyped US market is stoking the 'mother of all bubbles ...

    www.aol.com/overhyped-us-market-stoking-mother...

    Foreign investors are fueling the "mother of all bubbles" in US stocks, Ruchir Sharma wrote in the FT. "Global investors are committing more capital to a single country than ever before in modern ...

  9. Oversampling and undersampling in data analysis - Wikipedia

    en.wikipedia.org/wiki/Oversampling_and_under...

    For example, the individual components of a differential white blood cell count must all add up to 100, because each is a percentage of the total. Data that is embedded in narrative text (e.g., interview transcripts) must be manually coded into discrete variables that a statistical or machine-learning package can deal with.