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  2. Contrast (statistics) - Wikipedia

    en.wikipedia.org/wiki/Contrast_(statistics)

    A contrast is defined as the sum of each group mean multiplied by a coefficient for each group (i.e., a signed number, c j). [10] In equation form, = ¯ + ¯ + + ¯ ¯, where L is the weighted sum of group means, the c j coefficients represent the assigned weights of the means (these must sum to 0 for orthogonal contrasts), and ¯ j represents the group means. [8]

  3. Blend modes - Wikipedia

    en.wikipedia.org/wiki/Blend_modes

    The Luminosity mode is commonly used for image sharpening, because human vision is much more sensitive to fine-scale lightness contrast than color contrast. (See Contrast (vision) ) Few editors other than Photoshop implement this same color space for their analogs of these blend modes. [ 3 ]

  4. Absolute difference - Wikipedia

    en.wikipedia.org/wiki/Absolute_difference

    By contrast, simple subtraction is not non-negative or commutative, but it does obey the second and fourth properties above, since = if and only if =, and = + (). The absolute difference is used to define other quantities including the relative difference , the L 1 norm used in taxicab geometry , and graceful labelings in graph theory .

  5. Difference in differences - Wikipedia

    en.wikipedia.org/wiki/Difference_in_differences

    Difference in differences (DID [1] or DD [2]) is a statistical technique used in econometrics and quantitative research in the social sciences that attempts to mimic an experimental research design using observational study data, by studying the differential effect of a treatment on a 'treatment group' versus a 'control group' in a natural experiment. [3]

  6. Finite difference - Wikipedia

    en.wikipedia.org/wiki/Finite_difference

    In an analogous way, one can obtain finite difference approximations to higher order derivatives and differential operators. For example, by using the above central difference formula for f ′(x + ⁠ h / 2 ⁠) and f ′(x − ⁠ h / 2 ⁠) and applying a central difference formula for the derivative of f ′ at x, we obtain the central difference approximation of the second derivative of f:

  7. Cohen's h - Wikipedia

    en.wikipedia.org/wiki/Cohen's_h

    Describe the differences in proportions using the rule of thumb criteria set out by Cohen. [1] Namely, h = 0.2 is a "small" difference, h = 0.5 is a "medium" difference, and h = 0.8 is a "large" difference. [2] [3] Only discuss differences that have h greater than some threshold value, such as 0.2. [4]

  8. MaxDiff - Wikipedia

    en.wikipedia.org/wiki/MaxDiff

    In 1938 Richardson [2] introduced a choice method in which subjects reported the most alike pair of a triad and the most different pair. The component of this method involving the most different pair may be properly called "MaxDiff" in contrast to a "most-least" or "best-worst" method where both the most different pair and the direction of difference are obtained.

  9. Difference of two squares - Wikipedia

    en.wikipedia.org/wiki/Difference_of_two_squares

    In mathematics, the difference of two squares is a squared (multiplied by itself) number subtracted from another squared number. Every difference of squares may be factored according to the identity a 2 − b 2 = ( a + b ) ( a − b ) {\displaystyle a^{2}-b^{2}=(a+b)(a-b)}