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Greenhouse geissercorrection is the method of adjusting the degrees of freedom of the within- subject F-tests in the analysis of the variance of longitudinal data so as to allow the possible departures of the variance-covariance matrix of the measurements from the suppositions of sphericity. If this condition holds for data then the correction factor is one and the easy F-tests are valid. Departures from the sphericity result in the estimated correction factor less than one, hence reducing the degrees of freedom of the appropriate F-tests.
Mosaic displays is the graphical display of the standardized residuals from the fitting a log-linear model to a contingency table in which the colour and outline of the mosaic's '
moving and semi average method graphical reprsentation
Normality - Reasons for Screening Data Prior to analyzing multivariate normality, one should consider univariate normality Histogram, Normal Q-Qplot (values on x axis
Q1: The growth in bad debt expense for Aptara Pvt. Ltd. Company over the last 20 years is as follows. 1997 0.11 1998 0.09 1999 0.08 2000 0.08 2001 0.1 2002 0.11 2003 0.12 2004 0.1
The distribution free or technique which is the analogue of the analysis of variance for the design with two factors. It can be applied to data sets which do not meet the assumptio
The distribution over distributions in the sense that each draw from the process is itself the distribution. The name Dirichlet process or procedure is due to the fact that the ?ni
Household interview surveys : The surveys in which the primary sampling units are typically geographic regions such as nations or cities. For each such unit sampled, there are addi
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
How large would the sample need to be if we are to pick a 95% confidence level sample: (i) From a population of 70; (ii) From a population of 450; (iii) From a population of 1000;
MAREG is the software package for the analysis of the marginal regression models. The package permits the application of generalized estimating equations and the maximum likelihoo
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