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Median absolute deviation (MAD): It is the very robust estimator of the scale given by the following equation
or, in other words we can say that, the median of the absolute deviations from the median of data. In order to use MAD as the consistent estimator of the standard deviation it is multiplied by a scale factor which depends on the distribution of the data. For normally distributed data the constant is 1.4826 and expected value of 1.4826 MAD is approximately equal to population standard deviation.
Battery reduction : A common term for reducing the number of variables of the interest in a study for the purposes of study and perhaps later data collection. For instance, an over
distinguish the historigram and histogram
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
a psychic claims to be able to "feel colors" there are three pieces of colored paper(red, blue,green) he will place his hand on radomly selected pieces while blindfolded. you perfo
Assume that a population is normally distributed with a mean of 100 and a standard deviation of 15. Would it be unusual for the mean of a sample of 20 to be 115 or more?
A family of the probability distributions of the form given as here θ is the parameter and a, b, c, d are the known functions. It includes the gamma distribution, normal dis
In the experimental studies, the collection of individuals to which the experimental process of interest is not applied. In the observational studies, most often used for a collect
Window variables are the variables measured during the constrained interval of an observation period which is accepted as the proxies for the information over the whole period. Fo
Principal components analysis is a process for analysing multivariate data which transforms original variables into the new ones which are uncorrelated and account for decreasing
The Expectation/Conditional Maximization Either algorithm which is the generalization of ECM algorithm attained by replacing some of the CM-steps of ECM which maximize the constrai
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