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Negative binomial distribution is the probability distribution of number of failures, X, before the kth success in the sequence of Bernoulli trials where the probability of success at each trial is p and probability of failure is q =1-p. The distribution can be given as follows The mean, skewness, variance, and kurtosis of the distribution are as follows: Often used to model over the dispersion in count data.
Length-biased sampling : The bias which arises in the sampling scheme based on the visits of patient, when some individuals are more likely to be chosen than others simply because
Raking adjustments is an alternative to the post stratification adjustments in the complex surveys which ensures that the adjusted weights of the respondents conform to each of th
A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how t
The tabulation of a sample of observations in terms of numbers falling below particular values. The empirical equivalent of the growing probability distribution. An example of such
Lancaster models : The means of representing the joint distribution of the set of variables in terms of the marginal distributions, supposing all the interactions higher than a par
The division of a sample of observations into several classes, together with the number of observations in each of them. It acts as a useful summary of the main features of the da
Randomized response technique : The procedure for collecting the information on sensitive issues by means of the survey, in which an element of chance is introduced as to what quer
Response feature analysis is the approach to the analysis of longitudinal data including the calculation of the suitable summary measures from the set of repeated measures on each
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
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
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