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  2. 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).

  3. Effect size - Wikipedia

    en.wikipedia.org/wiki/Effect_size

    In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...

  4. Factor analysis - Wikipedia

    en.wikipedia.org/wiki/Factor_analysis

    The factor model must then be rotated for analysis. [4] Canonical factor analysis, also called Rao's canonical factoring, is a different method of computing the same model as PCA, which uses the principal axis method. Canonical factor analysis seeks factors that have the highest canonical correlation with the observed variables.

  5. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    "The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation". PeerJ Computer Science. 7 (e623): e623. doi: 10.7717/peerj-cs.623. PMC 8279135. PMID 34307865.

  6. Central composite design - Wikipedia

    en.wikipedia.org/wiki/Central_composite_design

    A factorial (perhaps fractional) design in the factors studied, each having two levels; A set of center points, experimental runs whose values of each factor are the medians of the values used in the factorial portion. This point is often replicated in order to improve the precision of the experiment;

  7. Variance inflation factor - Wikipedia

    en.wikipedia.org/wiki/Variance_inflation_factor

    Then, calculate the VIF factor for ^ with the following formula : = where R 2 i is the coefficient of determination of the regression equation in step one, with on the left hand side, and all other predictor variables (all the other X variables) on the right hand side.

  8. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    Designed experiments with full factorial design (left), response surface with second-degree polynomial (right) In statistics, a full factorial experiment is an experiment whose design consists of two or more factors, each with discrete possible values or "levels", and whose experimental units take on all possible combinations of these levels across all such factors.

  9. Coefficient of multiple correlation - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_multiple...

    The coefficient of multiple correlation is known as the square root of the coefficient of determination, but under the particular assumptions that an intercept is included and that the best possible linear predictors are used, whereas the coefficient of determination is defined for more general cases, including those of nonlinear prediction and those in which the predicted values have not been ...