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Graduation is the term is employed most often in the application of the actuarial statistics to denote procedures by which the set or group of observed probabilities is adjusted to give a appropriate basis for the inferences and the further practical calculations to be done.
Cauchy integral : The integral of the function, f (x), from a to b are de?ned in terms of the sum In the statistics this leads to the below shown inequality for the expecte
This is extension of the EM algorithm which typically converges more slowly than EM in terms of the iterations but can be much faster in the whole computer time. The general idea o
Random allocation is a technique for creating the treatment and control groups particularly in accordance of the clinical trial. Subjects receive the active treatment or the place
Designs in which the information on main effects and low-order inter- actions are attained by running only the fraction of the complete factorial experiment and supposing that part
A term commonly encountered in the application of the agglomerative hierarchical clustering techniques, where it refers to the 'tree-like' diagram illustrating the series of steps
Evaluate the following statistical arguments. Begin by identifying the sample, population, and the property which is being investigated. Do these arguments sound acceptable? Would
Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte
L'Abbe ´ plot is often used in the meta-analysis of the clinical trials where the result is the binary response of it. The event risk (number of events/number of the patients in a
Cause specific death rate : A death rate calculated for the people dying from the specific disease. For instance, the below given are the rates per 1000 people for three disease cl
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >
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