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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. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    Mathematically, linear least squares is the problem of approximately solving an overdetermined system of linear equations A x = b, where b is not an element of the column space of the matrix A. The approximate solution is realized as an exact solution to A x = b' , where b' is the projection of b onto the column space of A .

  4. Template:Square regular tiling table - Wikipedia

    en.wikipedia.org/wiki/Template:Square_regular...

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more

  5. Square-free element - Wikipedia

    en.wikipedia.org/wiki/Square-free_element

    The unique factorization property means that a non-zero non-unit r can be represented as a product of prime elements r = p 1 p 2 ⋯ p n {\displaystyle r=p_{1}p_{2}\cdots p_{n}} Then r is square-free if and only if the primes p i are pairwise non-associated (i.e. that it doesn't have two of the same prime as factors, which would make it ...

  6. Difference of two squares - Wikipedia

    en.wikipedia.org/wiki/Difference_of_two_squares

    The difference of two squares can also be used as an arithmetical short cut. If two numbers (whose average is a number which is easily squared) are multiplied, the difference of two squares can be used to give you the product of the original two numbers. For example: = (+)

  7. Explained sum of squares - Wikipedia

    en.wikipedia.org/wiki/Explained_sum_of_squares

    The explained sum of squares (ESS) is the sum of the squares of the deviations of the predicted values from the mean value of a response variable, in a standard regression model — for example, y i = a + b 1 x 1i + b 2 x 2i + ... + ε i, where y i is the i th observation of the response variable, x ji is the i th observation of the j th ...

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  9. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    In many cases, especially for smaller samples, the sample range is likely to be affected by the size of sample which would hamper comparisons. Another possible method to make the RMSD a more useful comparison measure is to divide the RMSD by the interquartile range (IQR). When dividing the RMSD with the IQR the normalized value gets less ...

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