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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. R-square - Wikipedia

    en.wikipedia.org/?title=R-square&redirect=no

    This page was last edited on 12 June 2006, at 01:51 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may ...

  4. Quintic function - Wikipedia

    en.wikipedia.org/wiki/Quintic_function

    Solving these two quintics yields r = 1.501 × 10 9 m for L 2 and r = 1.491 × 10 9 m for L 1. The Sun–Earth Lagrangian points L 2 and L 1 are usually given as 1.5 million km from Earth. If the mass of the smaller object ( M E ) is much smaller than the mass of the larger object ( M S ), then the quintic equation can be greatly reduced and L ...

  5. MAGA goes wild over Jill Biden’s very friendly encounter with ...

    www.aol.com/maga-goes-wild-over-jill-150426409.html

    Biden and Trump shared a moment caught on camera while waiting for French First Lady Brigitte Macron to take the seat that separated them during the reopening ceremony.

  6. Regularized least squares - Wikipedia

    en.wikipedia.org/wiki/Regularized_least_squares

    Regularized least squares (RLS) is a family of methods for solving the least-squares problem while using regularization to further constrain the resulting solution. RLS is used for two main reasons. The first comes up when the number of variables in the linear system exceeds the number of observations.

  7. NYT ‘Connections’ Hints and Answers Today, Friday, December 13

    www.aol.com/nyt-connections-hints-answers-today...

    Spoilers ahead! We've warned you. We mean it. Read no further until you really want some clues or you've completely given up and want the answers ASAP. Get ready for all of today's NYT ...

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