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The values assigned to factors for the individual sample units in a factor analysis. The most common approach is "regression method". When the factors are seen as the random variables this corresponds to the best linear unbiased predictor and if the factors are supposed to have normal distributions to the empirical Bayes prediction. The Bartlett technique is also sometimes used which corresponds to the max imum likelihood estimation of factor scores if the factors are seen as ?xed.
Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the
Paired samples are the two samples of the observations with the characteristic feature with each of the observation in one sample have only one matching observation in the other s
Hot deck is a method broadly used in surveys for imputing the missing values. In its easiest form the method includes sampling with replacement m values from the sample respondent
Glim is the software package specifically suited for fitting the generalized linear models (the acronym stands for the Generalized Linear Interactive Modelling), including the log
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A procedure whereby the collection of multiple sample units are combined in their entirety or in part, to form the new sample. One or more succeeding measurements are taken on the
How is the rejection region defined and how is that related to the z-score and the p value? When do you reject or fail to reject the null hypothesis? Why do you think statisticians
Prognostic scoring system is a technique of combining the prognostic information contained in the number of threat factors, in a manner which best predicts each patient's risk of
Surveys which use lists related with the vital statistics to sample individuals for the further information. For instance, the 1988 National Mortality Follow back Survey sampled de
The generalization of the normal distribution used for the characterization of functions. It is known as a Gaussian process because it has Gaussian distributed finite dimensional m
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