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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 predicted value in terms of the model of interest. It is often used when the variance of response variable is thought to change over range of values of the explanatory variable(s), in which case the weights are usually taken as the reciprocals of the variance.
Line-intersect sampling is a technique of unequal probability sampling for selecting the sampling units in the geographical area. A sample of lines is drawn in a study area and, w
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Prospective study : The studies in which individuals are followed-up over the period of time. A general example of this type of investigation is where the samples of individuals ar
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
The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial inte
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 interplay of the genes and environment on, for instance, the risk of disease. The term represents the step away from the argument as to whether the nature or nurture is the pre
The model which arises in the context of estimating the size of the closed population where individuals within the population could be identified only during some of the observatio
Hosmer-Lemeshow test is a goodness-of-fit test taken in use in logistic regression, particularly when there are regular covariates. Units are spitted into deciles based on predict
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