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  2. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.

  3. 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 ...

  4. Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_determination

    Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).

  5. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    A properly conducted regression analysis will include an assessment of how well the assumed form is matched by the observed data, but it can only do so within the range of values of the independent variables actually available.

  6. Regression discontinuity design - Wikipedia

    en.wikipedia.org/.../Regression_discontinuity_design

    Note that regression kinks (or kinked regression) can also mean a type of segmented regression, which is a different type of analysis. Final considerations. The RD design takes the shape of a quasi-experimental research design with a clear structure that is devoid of randomized experimental features.

  7. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    One of the most important requirements of experimental research designs is the necessity of eliminating the effects of spurious, intervening, and antecedent variables. In the most basic model, cause (X) leads to effect (Y). But there could be a third variable (Z) that influences (Y), and X might not be the true cause at all.

  8. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Analysis refers to dividing a whole into its separate components for individual examination. [10] Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11]

  9. Replication crisis - Wikipedia

    en.wikipedia.org/wiki/Replication_crisis

    This is because research design and data analysis entail numerous decisions that are not sufficiently constrained by a field’s best practices and statistical methodologies. As a result, researcher DF can lead to situations where some failed replication attempts use a different, yet plausible, research design or statistical analysis; such ...