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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 type of longitudinal study in which the subjects receive different treatments on the various occasions. Random allocation is required to determine the order in which the treatm
Sam Tyler, a single taxpayer, social security number 111-44-1111, bought Rental Equipment on 04/01/2010. He paid $400,000 including all closing and delivery costs. In the current y
The procedure in which the prior distribution is required in the application of Bayesian inference, it is determined from empirical evidence, namely same data for which the posteri
The problem that the studies are not uniformly probable to be published in the scientific journals. There is evidence that the statistical significance is a main determining factor
An auditor for a government agency needs to evaluate payments for doctors' office visits paid by Medicare in a small regional town during the month of June. A total of 25,056 visit
Coincidences : Astonishing concurrence of the events, perceived as meaningfully related, with no apparent causal connection. Such type of events abounds in everyday life and is oft
difference between histogram and historigram
Percentile : The set or group of divisions which produce exactly 100 equal parts in the series of continuous values, like blood pressure, height, weight, etc. Hence a person with b
Time series : The values of a variable recorded, generally at a regular interval, over the long period of time. The observed movement and fluctuations of several such series are
The measure of the degree to which the particular model differs from the saturated model for the data set. Explicitly in terms of the likelihoods of the two models can be defined a
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