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Interior analysis is the term now and again applied to analysis carried out on the fitted model in regression problem. The basic target of such analyses is the identification of the problem regions with respect to original least squares fit of the fitted model. Of particular interest is the disposition of the individual data points and their relative influence on the global measures used as the guides in subsequent stages of estimates of parameters in the successive models. Outliers from the fitted or predicted response, multivariate outliers among explanatory variables, and the points in the space of explanatory variables with great leverage on the fitted model must be recognized, and their influence evaluated before further analysis is under- taken.
Difference b/w historigram and histogram
Human height growth curves : The growth of human height is, in common, remarkably regular, apart from the pubertal growth spurt. The satisfactory longitudinal development curve is
Weighted least squares is the method of estimation in which the estimates arise from minimizing the weighted sum of squares of the differences between response variable and its pr
2 jobs n machines,graphical method,how to determine which job should proceed first on each machine
Resentful demoralization is the possible phenomenon in the clinical trials and intervention studies in which comparison groups not attaining a perceived desirable treatment become
The distribution free or technique which is the analogue of the analysis of variance for the design with two factors. It can be applied to data sets which do not meet the assumptio
Initial data analysis (IDA): The first phase in the examination of the data set which comprises number of informal steps including the following steps * checking the quality o
A term commonly encountered in the analysis of the contingency tables. Such type of frequencies are the estimates of the values to be expected under hypothesis of interest. In a tw
Persson Rootze ´n estimator is an estimator for the parameters in the normal distribution when the sample is truncated so that all the observations under some fixed value C are re
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
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