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The average student grade can be obtained by averaging all the grades, without regard to classes (add all the grades up and divide by the total number of students): ¯ = = Or, this can be accomplished by weighting the class means by the number of students in each class.
The Marshall-Edgeworth index, credited to Marshall (1887) and Edgeworth (1925), [11] is a weighted relative of current period to base period sets of prices. This index uses the arithmetic average of the current and based period quantities for weighting. It is considered a pseudo-superlative formula and is symmetric. [12]
The overall grade for the class is then typically weighted so that the final grade represents a stated proportion of different types of work. For example, daily homework may be counted as 50% of the final grade, chapter quizzes may count for 20%, the comprehensive final exam may count for 20%, [1] and a major project may count for the remaining ...
The WPGMA algorithm constructs a rooted tree that reflects the structure present in a pairwise distance matrix (or a similarity matrix).At each step, the nearest two clusters, say and , are combined into a higher-level cluster .
The unbiased weighted estimator of the sample variance can be computed as follows: = = (=) = = (¯). Again, the corresponding standard deviation is the square root of the variance.
A power mean serves a non-linear moving average which is shifted towards small signal values for small p and emphasizes big signal values for big p. Given an efficient implementation of a moving arithmetic mean called smooth one can implement a moving power mean according to the following Haskell code.
Weighted least squares (WLS), also known as weighted linear regression, [1] [2] is a generalization of ordinary least squares and linear regression in which knowledge of the unequal variance of observations (heteroscedasticity) is incorporated into the regression.
Note that the unweighted term indicates that all distances contribute equally to each average that is computed and does not refer to the math by which it is achieved. Thus the simple averaging in WPGMA produces a weighted result and the proportional averaging in UPGMA produces an unweighted result ( see the working example ).