9/18/2023 0 Comments R standard deviation![]() ![]() In classical and usual random sample, the degree of belonging xi into the random sample is equal to 1, for 1 \leq i \leq n. Also, each element of mu must be in interval. Assume that x(x1, x2, \cdots, xn) is the observed value of a random sample from a fuzzy population. The weighted standard deviation of vector x, by considering weights vector mu, is numeric or a vector of length one. The length of this vector must be equal to the length of data and each element of it is belongs to interval. Therefore in such situations, it is more appropriate that we show the observed value of the random sample by notation \ by formulaĪ vector-valued numeric data which you want to compute its weighted standard deviation.Ī vector of weights. In R, the standard deviation can be calculated making use of the sd function, as shown below: Sample vector x <- c(10, 25, 12, 18, 5, 16, 14, 20) Standard deviation sd(x. In classical and usual random sample, the degree of belonging x_i into the random sample is equal to 1, for 1 \leq i \leq n.īut considering fuzzy population, we denote the degree of belonging x_i into the fuzzy population (or into the observed value of random sample) by \mu_i which is a real-valued number from. The standard deviation is more used in Statistics than the variance, as it is expressed in the same units as the variable, while the variance is expressed in square units. Assume that x=(x_1, x_2, \cdots, x_n) is the observed value of a random sample from a fuzzy population. ![]()
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