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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.
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-weighted average of the values the function takes on for each possible value of the random variable.
In statistics, there are many applications of "weighting": Weighted mean; Weighted harmonic mean; Weighted geometric mean; Weighted least squares
the arithmetic mean of data values after a certain number or proportion of the highest and lowest data values have been discarded. Interquartile mean a truncated mean based on data within the interquartile range. Midrange the arithmetic mean of the maximum and minimum values of a data set. Midhinge the arithmetic mean of the first and third ...
In statistics, the weighted geometric mean is a generalization of the geometric mean using the weighted arithmetic mean. Given a sample = ...
Advanced Placement (AP) Statistics (also known as AP Stats) is a college-level high school statistics course offered in the United States through the College Board's Advanced Placement program. This course is equivalent to a one semester, non- calculus -based introductory college statistics course and is normally offered to sophomores , juniors ...
If one rolls the die times and computes the average (arithmetic mean) of the results, then as grows, the average will almost surely converge to the expected value, a fact known as the strong law of large numbers. The roulette game consists of a small ball and a wheel with 38 numbered pockets around the edge. As the wheel is spun, the ball ...
One very early weighted estimator is the Horvitz–Thompson estimator of the mean. [3] When the sampling probability is known, from which the sampling population is drawn from the target population, then the inverse of this probability is used to weight the observations. This approach has been generalized to many aspects of statistics under ...