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Principal components analysis is a process for analysing multivariate data which transforms original variables into the new ones which are uncorrelated and account for decreasing the proportions of variance in the data. The goal of the method is to decrease the dimensionality of the data. The principal components, new variables, are defined as the linear functions of the usual variables. If the first few principal components account for the large percentage of the variance of the observations (say it above 70%) they can be used both to simplify subsequent analyses and to display and summarize the data in a parsimonious way.
The plot of the number of cases of the disease against the time period. A large and sudden increase corresponds to an epidemic. The example of this is shown in the figure drawn bel
Poisson regression In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regre
National lotteries : Games of chance held to heave money for particular causes. The first held in the UK took place in the year 1569 principally to raise money for repair of the Ci
This is an alternative to the Newton-Raphson technique for optimization (finding out the minimum or the maximum) of some function, which includes replacing the matrix of second der
a company suppliers specialized, high tensile Pins to customers. It uses an automatic lathe to produce the pins. Due to the factors such as vibration, temperature and wear and tear
Conjoint analysis : The method used basically in market research which is similar in many respects to the various dimensional scaling. The method attempts to assign values to the l
Geographical analysis machine is the procedure designed to detect the clusters of rare diseases in a particular area. Circles of fixed radii are created at each point of the squar
Link functions: The link function relates the linear predictor ηi to the expected value of the data. In classical linear models the mean and the linear predictor are identical
The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
Method of moments is the procedure for estimating the parameters in a model by equating sample moments to the population values. A famous early instance of the use of the proced
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