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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.
This term applied in the context of comparing the different methods and techniques of estimating the same parameter; the estimate with the lowest variance being regarded as the mos
Last observation carried forward is a technique for replacing the observations of the patients who drop out of the clinical trial carried out over a time period. It consists of su
Balanced incomplete block design : A design in which all the treatments are not used in all blocks. Such designs have the below stated properties: * each block comprises the
Raking adjustments is an alternative to the post stratification adjustments in the complex surveys which ensures that the adjusted weights of the respondents conform to each of th
Bubble plot : A method or technique for displaying the observations which involve three variable values. Two of the variables are used to make a scatter diagram and values of the t
Coefficient of concordance : The coef?cient is taken in use to assess the agreement among m raters ranking n individuals according to some of the speci?c characteristic. Which can
Mention the characteristics of Statistics. Explain any two applications of Statistics.
Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the
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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
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