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  2. Weighted arithmetic mean - Wikipedia

    en.wikipedia.org/wiki/Weighted_arithmetic_mean

    The weighted mean in this case is: ¯ = ¯ (=), (where the order of the matrix–vector product is not commutative), in terms of the covariance of the weighted mean: ¯ = (=), For example, consider the weighted mean of the point [1 0] with high variance in the second component and [0 1] with high variance in the first component.

  3. Weight function - Wikipedia

    en.wikipedia.org/wiki/Weight_function

    The maximum likelihood method weights the difference between fit and data using the same weights . The expected value of a random variable is the weighted average of the possible values it might take on, with the weights being the respective probabilities. More generally, the expected value of a function of a random variable is the probability ...

  4. Kernel smoother - Wikipedia

    en.wikipedia.org/wiki/Kernel_smoother

    Kernel average smoother example. The idea of the kernel average smoother is the following. For each data point X 0, choose a constant distance size λ (kernel radius, or window width for p = 1 dimension), and compute a weighted average for all data points that are closer than to X 0 (the closer to X 0 points get higher weights).

  5. HP 35s - Wikipedia

    en.wikipedia.org/wiki/HP_35s

    The 35s's statistics capabilities are fairly standard. It can process a set of one-variable or two-variable statistics. Calculated results include means, weighted mean, standard deviation, and linear regression figures. The summation registers are also accessible for further calculations.

  6. Reduced chi-squared statistic - Wikipedia

    en.wikipedia.org/wiki/Reduced_chi-squared_statistic

    In data analysis based on the Rasch model, the reduced chi-squared statistic is called the outfit mean-square statistic, and the information-weighted reduced chi-squared statistic is called the infit mean-square statistic.

  7. Weighted statistics - Wikipedia

    en.wikipedia.org/wiki/Weighted_statistics

    In statistics, there are many applications of "weighting": Weighted mean; Weighted harmonic mean; Weighted geometric mean; Weighted least squares

  8. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    Since the probabilities must satisfy p 1 + ⋅⋅⋅ + p k = 1, it is natural to interpret E[X] as a weighted average of the x i values, with weights given by their probabilities p i. In the special case that all possible outcomes are equiprobable (that is, p 1 = ⋅⋅⋅ = p k), the weighted average is given by the standard average. In the ...

  9. Weighted median - Wikipedia

    en.wikipedia.org/wiki/Weighted_median

    The lower weighted median is 2 with partition sums of 0.49 and 0.5, and the upper weighted median is 3 with partition sums of 0.5 and 0.25. In the case of working with integers or non-interval measures, the lower weighted median would be accepted since it is the lower weight of the pair and therefore keeps the partitions most equal. However, it ...