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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. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Pearson_correlation...

    Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.

  4. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    The formulas given in the previous section allow one to calculate the point estimates of α and β — that is, the coefficients of the regression line for the given set of data. However, those formulas do not tell us how precise the estimates are, i.e., how much the estimators α ^ {\displaystyle {\widehat {\alpha }}} and β ^ {\displaystyle ...

  5. Correlation - Wikipedia

    en.wikipedia.org/wiki/Correlation

    Some correlation statistics, such as the rank correlation coefficient, are also invariant to monotone transformations of the marginal distributions of X and/or Y. Pearson/Spearman correlation coefficients between X and Y are shown when the two variables' ranges are unrestricted, and when the range of X is restricted to the interval (0,1).

  6. 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.

  7. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    This approximate formula is for moderate to large sample sizes; the reference gives the exact formulas for any sample size, and can be applied to heavily autocorrelated time series like Wall Street stock quotes. Moreover, this formula works for positive and negative ρ alike. [12] See also unbiased estimation of standard deviation for more ...

  8. Y-factor - Wikipedia

    en.wikipedia.org/wiki/Y-factor

    In the Y-factor technique, P out is measured for two different, known values of T R. P out is then converted to an effective temperature T out (in units of kelvin) by dividing by k B and the measurement bandwidth B. The two values of T out are then plotted as a function of T R (also in units of kelvin), and a line is fit to these points (see ...

  9. Confidence interval - Wikipedia

    en.wikipedia.org/wiki/Confidence_interval

    Suppose we wanted to calculate a 95% confidence interval for . First, let c {\displaystyle c} the 97.5th percentile of the distribution of T {\displaystyle T} . Then there is a 2.5% chance that T {\displaystyle T} will be less than − c {\displaystyle -c} and a 2.5% chance that it will be larger than + c . {\displaystyle +c.}