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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. Pseudo-R-squared - Wikipedia

    en.wikipedia.org/wiki/Pseudo-R-squared

    The last value listed, labelled “r2CU” is the pseudo-r-squared by Nagelkerke and is the same as the pseudo-r-squared by Cragg and Uhler. Pseudo-R-squared values are used when the outcome variable is nominal or ordinal such that the coefficient of determination R 2 cannot be applied as a measure for goodness of fit and when a likelihood ...

  4. 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 ...

  5. Least squares - Wikipedia

    en.wikipedia.org/wiki/Least_squares

    The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. In regression analysis, least squares is a parameter estimation method based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each ...

  6. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    In bioinformatics, the root mean square deviation of atomic positions is the measure of the average distance between the atoms of superimposed proteins. In structure based drug design, the RMSD is a measure of the difference between a crystal conformation of the ligand conformation and a docking prediction.

  7. Adjusted Gross Income: What It Is and How To Calculate ... - AOL

    www.aol.com/adjusted-gross-income-calculate...

    What Is the Difference Between Gross Income and Adjusted Gross Income? Gross income is the total amount of money you earn before deductions like FICA tax, employer benefits and contributions to ...

  8. Adjusted Gross Income (AGI) vs. Modified Adjusted Gross ... - AOL

    www.aol.com/finance/adjusted-gross-income-agi-vs...

    A woman researching the differences between MAGI vs. AGI before filing her taxes. Adjusted gross income (AGI) and modified adjusted gross income (MAGI) are two ways to calculate what your income ...

  9. Talk:Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Talk:Coefficient_of...

    Who says R-squared should be greater than zero? For example if measured y-values are between 9 and 10, and model prediction is always zero, then R-squared is heavily negative.Kokkokanta 07:50, 28 January 2007 (UTC) >> Go back and look at the definition. For one thing, all the sums are of squared differences. Moreover, SSE<=SST by construction.