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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.
The term used when the aggregated data (for instance, aggregated over different areas) are analysed and the results supposed to apply to the relationships at the individual level.
Cause specific death rate : A death rate calculated for the people dying from the specific disease. For instance, the below given are the rates per 1000 people for three disease cl
1. define statistical algorithms 2. write the flow charts for statistical algorithms for sums, squares and products. 3. write flow charts for statistical algorithms to generates ra
Mosaic displays is the graphical display of the standardized residuals from the fitting a log-linear model to a contingency table in which the colour and outline of the mosaic's '
The method or technique for displaying the relationships between categorical variables in a type of the scatter plot diagram. For two this type of variables displayed in the form o
The procedure in which initially the sample of subjects is selected for generating the auxillary information only, and then the second sample is selected in which the variable of i
facts and statistics about daycare
An unusual aggregation of the health events, real or perceived. The events might be grouped in the particular region or in some short period of time, or they might happen among the
Mardia's multivariate normality test is a test that a set of the multivariate data arise from the multivariate normal distribution against departures due to the kurtosis. The test
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
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