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Normality - Reasons for Screening Data
Prior to analyzing multivariate normality, one should consider univariate normality
Multivariate normality refers to a normal distribution of combination of variables (two-by-two, plus all linear combination of the variables) Univariate normality is a necessary but not sufficient condition for multivariate normality.
For bivariate normality one should check all the two-by-two scatter plots (they should have elliptical shape)
Sometimes data transformation is necessary for normality.
when there is tie in sequencing then what we do
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
show all the ways in which 3 games of football can be concluded(it can be a win W,a loss L,or a draw X)
CONSTRUCTION OF AN OR MODEL
Pie chart is an extensively used graphical technique for presenting relative frequencies related with the observed values of the categorical variable. The chart comprises of a cir
The model which is applicable to the longitudinal data in which the dropout process might give rise to the informative lost values. Specifically if the study protocol specifies the
The probability distribution which is a linear function of the number of component probability distributions. This type of distributions is used to model the populations thought to
Particlefilters is a simulation method for tracking moving target distributions and for reducing computational burden of the dynamic Bayesian analysis. The method uses a Markov ch
Glejser test is the test for the heteroscedasticity in the error terms of the regression analysis which involves regressing the absolute values of the regression residuals for the
Relative risk is the measure of the association between the exposure to a particular factor and the risk or probability of a convinced outcome, calculated as follows therefor
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