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Negative hyper geometric distribution: In sampling without replacement from the population comprising of r elements of one kind and N - r of another, if two elements corresponding to which selected are replaced every time, then the probability of finding x elements of first kind in a random sample of n elements can be given as follows
The mean of distribution can be given as Nr/N and the variance can be given as follows (nr/N)(1-r/N)(N+n)/(N+1).
It corresponds to the beta binomial distribution with the integral parameter values.
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
Cauchy distribution : The probability distribution, f (x), can be given as follows where α is the position of the parameter (median) and the beta β a scale parameter. Moments
A comprehensive regression analysis of the case study London has been carried out to test the 4 assumptions of regression: 1. Variables are normally distributed 2. Linear rel
Path analysis is a device for evaluating the interrelationships among the variables by analyzing their correlational structure. The relationships between the variables are man
Chains of infection : The description of the course of infection among the group of individuals. The susceptibles infected by the direct contact with the introductory cases are sai
methods of measuring trend
An approach to investigations designed to recognize a particular medical condition in the large population, usually by means of a blood test, which might result in the considerable
Perturbation theory : The theory useful in assessing how well a specific algorithm or the statistical model performs when the observations suffer less random changes. In very commo
The results of a survey determined whether the age of a driver 21 years and older has any effect on the number of motor vehicle accidents in which he/she is involved. Question 1:
The measure of the degree to which the particular model differs from the saturated model for the data set. Explicitly in terms of the likelihoods of the two models can be defined a
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