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Principal factor analysis is the method of factor analysis which is basically equivalent to a principal components analysis performed on reduced covariance matrix attained by replacing the diagonal elements of the sample variance-covariance matrix with the estimated communalities.
The two often used estimates of the latter are (a) the square of the multiple correlation coefficient of ith variable with all the other variables, (b) the largest of the absolute values of the correlation coefficients between the ith variable and one of other variables
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The scatter plot of SRES1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plot show that th
This is the theorem which states that if the error terms in a multiple regression have the same variance and are not corrected, then the estimators of the parameters in the model p
MAZ experiments : The Mixture-amount experiments which include control tests for which the entire amount of the mixture is set to zero. Examples comprise drugs (some patients do no
Literature controls : The patients with the disease of interest who have received, in the past, one of two treatments under the investigation, and for whom the results have been pu
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
Centile reference charts : Charts which are used inmedicine to observe the clinical measurements on individual patients in the context of the population values. If the population i
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
Designs in which the information on main effects and low-order inter- actions are attained by running only the fraction of the complete factorial experiment and supposing that part
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