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Clinical vs. statistical significance: The distinction among results in terms of their possible clinical importance rather than simply in terms of their statistical importance. With large samples, for instance, very small differences which have little or no clinical importance may turn out to be the statistically signi?cant products. The practical implications of any ?nding in the medical investigation should be judged on the clinical as well as the statistical grounds.
Kaiser's rule is the rule frequently used in the principal components analysis for selecting the suitable the number of components. When the components are derived from correlati
The more effective display than a number of other methods or techniques, for instance, pie charts and bar charts, for displaying the quantitative data which are labeled. An instanc
Non linear mapping (NLM ) is a technique for obtaining a low-dimensional representation of the set of multivariate data, which operates by minimizing a function of the differences
Causality: The relating of the reasons to the effects they produce. Several investigations in medicine seek to establish the causal relations between the events, for instance, whi
Uncertainty analysis is the process for assessing the variability in the outcome variable that is due to the uncertainty in estimating the values of input parameters. A sensitivit
Likert scales is often used in the studies of attitudes in which the raw scores are based on the graded alternative responses to each of a series of queries. For instance, the sub
Human capital model : The model for evaluating the economic implication of the disease in terms of the economic loss of a person succumbing to morbidity or the mortality at some pa
Suppose we estimate the following model: Passengersi = 1 + 2Populationi + ui a) Generate a scatter plot with passengers on the vertical axis and population on the horizonta
what are all the organs
The graphic representation of the alternatives in a decision making problem which summarizes all the possibilities foreseen by the decision maker. For instance, suppose we are give
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