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Outlier is an observation which seems to deviate markedly from the other members of the sample in which it happens. In the set of systolic blood pressures, {125, 128, 130, 131, 198}, for instance, 198 might be considered an outlier. More formally the term refers to the observation which seems to be inconsistent with the rest of the data, relative to a supposed model. Such extreme observations might be reflecting some abnormality in the measured characteristic of the subject, or they might result from an error in the measurement or recording.
Lexis diagram is the diagram for displaying the simultaneous effects of the two time scales (generally age and calendar time) on a rate. For instance, mortality rates from cancer
Post stratification adjustmen t: One of the most often used population weighting adjustments used in the complex surveys, in which weights for the elements in a class are multiplie
Helmert contrast is the contrast often used in analysis of the variance, in which each level of a factor is tested against average of the remaining levels. So, for instance, if th
It is the art of attempting to exchange something quite small and certain, for something which are large and uncertain. Gambling is big business; in the US, for instance, it is at
1. The production manager of Koulder Refrigerators must decide how many refrigerators to produce in each of the next four months to meet demand at the lowest overall cost. There i
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
O'Brien's two-sample tests are the extensions of the conventional tests for assessing the differences between treatment groups which take account of the possible heterogeneous nat
The alternative process to make use of the chi-squared statistic for assessing the independence of the two variables forming a two-by-two contingency table particularly when expect
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 repl
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
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