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A vague concept which occurs all through statistics. Essentially the term means the number of independent units of the information in an easy relevant to the estimation of the parameter or calculation of a statistic. For instance, in a two-by-two contingency table with the provided set of marginal totals, only one out of the four cell frequencies is free and the table has thus a single degree of freedom. In number of cases the term corresponds to the number of parameters in the model. It is also used to refer to a parameter of the various families of distributions such as, Student's t-distribution and the F- distribution.
Cohort study : An investigation in which the group of individuals (or the cohort) is identi?ed and followed prospectively, possibly for many years, and their subsequent medical his
Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of
High-dimensional data : This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21 st
Multimodal distribution is the probability distribution or frequency distribution with number of modes. Multimodality is frequently taken as an indication which the observed di
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 nR2 > MTB >
Play-the-winner rule is a process sometimes considered in the clinical trials in which the response to treatment is positive (a success) or negative (a failure). One of two treatm
Option-3 scheme is a scheme of measurement used in the situations investigating possible changes over the time in longitudinal data. The scheme is planned to prevent measurement o
t distribution
A comprehensive regression analysis of the case study London has been carried out to test the 4 assumptions of regression: 1. Variables are normally distributed 2. Linear rel
Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing
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