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Quality control procedures is the statistical process designed to ensure that the precision and accuracy of, for instance, a laboratory test, are maintained within the acceptable limits. The simplest such process involves the chart (generally called a control chart) with three horizontal lines, one made at the target level of the applicable control statistic, and the others, called action lines, made at some pre-specified distance above and below the target level. The procedure is examined to be at an acceptable quality level as long as the observed control statistic lies among the two lines and to be at a rejectable quality level if any of these lines are crossed.
Range is the difference between the largest and smallest observations in the data set. Commonly used as an easy-to-calculate measure of the dispersion in the set of observations b
Kolmogorov Smirnov two-sample method is a distribution free technique which tests for any difference between the two populations probability distributions. The test is relied on t
Quittingill effect is a problem which occurs most frequently in studies of the smoker cessation where smokers frequently quit smoking following the onset of the disease symptoms
Collapsing categories : A procedure generally applied to contingency tables in which the two or more row or column categories are combined, in number of cases so as to yield the re
Evaluate the following statistical arguments. Begin by identifying the sample, population, and the property which is being investigated. Do these arguments sound acceptable? Would
Lagrange Multiplier (LM) test The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1
Normal 0 false false false EN-US X-NONE X-NONE
Cartogram : It is the diagram in which descriptive statistical information is displayed on the geographical map by the means of shading, different symbols or in some other possibly
Two-phase sampling is the sampling scheme including two distinct phases, in the first of which the information about the particular variables of interest is collected on all the m
K-means cluster analysis is the method of cluster analysis in which from an initial partition of observations into K clusters, each observation in turn is analysed and reassigned,
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