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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.
4-13. Students in a management science class have just received their grades on the first test. The instructor has provided information about the first test grades in some previou
This is the branch of mathematics which deals with the theory of contests between two or more players under the specified sets of rules. The subject supposes a statistical aspect w
Bayes factor : A summary of evidence for the modelM1 against the another modelM0 provided by the set of data D, which can be used in the model selection. Given by the ratio of post
Paired availability design is a design which can lessen selection bias in the situations where it is not possible to use random allocation of the subjects to treatments. The desig
Homoscedasticity - Reasons for Screening Data Homoscedasticity is the assumption that the variability in scores for a continuous variable is roughly the same at all values of
Cluster analysis : A set of methods or techniques for constructing a sensible and informative classi?cation of an initially unclassi?ed set of data, using variable values observed
There are two periods. You observe that Jack consumes 100 apples in period t = 0, and 120 apples in period t = 1. That is, (c 0 ; c 1 ) = (100; 120) Suppose Jack has the util
Bayesian confidence interval : An interval of the posterior distribution which is so that the density of it at any point inside the interval is greater than that of the density at
HOW TO CONSTRUCT A BIVARIATE FREQUENCY DISTRIBUTION
This is the theorem which states that if the error terms in a multiple regression have the same variance and are not corrected, then the estimators of the parameters in the model p
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