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  2. Cross-sectional data - Wikipedia

    en.wikipedia.org/wiki/Cross-sectional_data

    Cross-sectional data can be used in cross-sectional regression, which is regression analysis of cross-sectional data. For example, the consumption expenditures of various individuals in a fixed month could be regressed on their incomes, accumulated wealth levels, and their various demographic features to find out how differences in those ...

  3. 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.

  4. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    By splitting the data into multiple parts, we can check if an analysis (like a fitted model) based on one part of the data generalizes to another part of the data as well. [144] Cross-validation is generally inappropriate, though, if there are correlations within the data, e.g. with panel data . [ 145 ]

  5. Oversampling and undersampling in data analysis - Wikipedia

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

    Within statistics, oversampling and undersampling in data analysis are techniques used to adjust the class distribution of a data set (i.e. the ratio between the different classes/categories represented). These terms are used both in statistical sampling, survey design methodology and in machine learning.

  6. 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.

  7. 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."

  8. Simpson's paradox - Wikipedia

    en.wikipedia.org/wiki/Simpson's_paradox

    Despite these criticisms, the apparent Simpson's paradox remains a popular and intriguing topic in statistics and data analysis. It continues to be studied and debated by researchers and practitioners in a wide range of fields, and it serves as a valuable reminder of the importance of careful statistical analysis and the potential pitfalls of ...

  9. List of analyses of categorical data - Wikipedia

    en.wikipedia.org/wiki/List_of_analyses_of...

    Cochran–Armitage test for trend; Cochran–Mantel–Haenszel statistics; Correspondence analysis; Cronbach's alpha; Diagnostic odds ratio; G-test; Generalized estimating equations; Generalized linear models; Krichevsky–Trofimov estimator; Kuder–Richardson Formula 20; Linear discriminant analysis; Multinomial distribution; Multinomial ...