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is the sum of an arithmetico-geometric series defined by = =, =, and =, and it converges to =. This sequence corresponds to the expected number of coin tosses required to obtain "tails". The probability T k {\displaystyle T_{k}} of obtaining tails for the first time at the k th toss is as follows:
Different labs use different formulas and procedures to calculate the anion gap, so the reference range (or "normal" range) from one lab isn't directly interchangeable with the range from another. The reference range provided by the particular lab that performed the testing should always be used to interpret the results. [ 3 ]
The geometric series is an infinite series derived from a special type of sequence called a geometric progression.This means that it is the sum of infinitely many terms of geometric progression: starting from the initial term , and the next one being the initial term multiplied by a constant number known as the common ratio .
The probability distribution of the sum of two or more independent random variables is the convolution of their individual distributions. The term is motivated by the fact that the probability mass function or probability density function of a sum of independent random variables is the convolution of their corresponding probability mass functions or probability density functions respectively.
This means that the sum of two independent normally distributed random variables is normal, with its mean being the sum of the two means, and its variance being the sum of the two variances (i.e., the square of the standard deviation is the sum of the squares of the standard deviations). [1]
It may be used to prove Nicomachus's theorem that the sum of the first cubes equals the square of the sum of the first positive integers. [2] Summation by parts is frequently used to prove Abel's theorem and Dirichlet's test.
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For example, for a Gaussian distribution with unknown mean and variance, the jointly sufficient statistic, from which maximum likelihood estimates of both parameters can be estimated, consists of two functions, the sum of all data points and the sum of all squared data points (or equivalently, the sample mean and sample variance).