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Probability distribution: For the discrete random variable, a mathematical formula which provides the probability of each value of variable. See, for instance, binomial distribution and Poisson distribution. For the continuous random variable, a curve described by the mathematical formula which specifies, by way of area under the curve, the probability which the variable falls within the particular interval. Examples comprise the normal distribution and the exponential distribution. In both the cases the term probability density might also be used. (A distinction is sometimes made among 'density' and 'distribution', when the latter is reserved for probability that the random variable comes below some value. In this dictionary, though, the latter will be termed the cumulative probability distribution and the probability distribution and probability density both are used synonymously.
how to describe association between quantitative and categorical variables
This is an attempt to measure the suffering caused by the illness which takes into the account both the years of the potential life lost due to the premature mortality as well as t
stationary time series
Please help with following problem: : Let’s consider the logistic regression model, which we will refer to as Model 1, given by log(pi / [1-pi]) = 0.25 + 0.32*X1 + 0.70*X2 + 0.
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Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights
Genstat: The basic purpose piece of statistical software for the management and the analysis of data. The package incorporates the wide variety of data handling events and a wi
For a career woman, wearing lipstick has become an integral part of her daily life. It is not unusual for a woman to look for a lipstick that will stay on her lips and not smudge
Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte
1) Let N1(t) and N2(t) be independent Poisson processes with rates, ?1 and ?2, respectively. Let N (t) = N1(t) + N2(t). a) What is the distribution of the time till the next epoch
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