Saddlepoint Approximation for the Distribution of the Sum of Independent Random Variables
," Advances in Applied Probability, 475-490, 1980.
2] are two independent random variables
of uniform distribution over [0, 1].
The Central Limit Theorem, a classical result in probability theory, tells us that the distribution of a sum of several independent random variables
tends towards Gaussian distribution, under certain conditions.
n] is a discrete structure, such as a permutation or a graph, and where the input values are realizations of independent random variables
with the same distribution, the output sequence is a Markov chain X = ([X.
2]) represents a white noise, a series of independent random variables
, identically distributed: E[[epsilon].
2](x) of two independent random variables
with Gaussian distribution has also Gaussian distribution
Shao  proved a comparison theorem on maximal inequalities between negatively associated and independent random variables
, and obtained the Rosenthal-typemaximal inequality and the Kolmogorov exponential inequality.
It omits materialaon probability and probability distributions, independent random variables
, weighted sums of random variables, fitting a probability distribution to data with @RISK, one-way ANOVA (discussed online), theapartial F test, and auto regression models.
In the end, we derive results on products and quotients of independent random variables
Table 6 presents the reliability index [beta] regarding different values of the coefficient of variation for independent random variables
k] ([omega])'s are real and independent random variables
with mean zero and variance one.
We further assume, that ti delays are independent random variables
, hence (by the law of large numbers--(Ventsel, 1969)) the sum (10) is a normally distributed random variable with parameters