pebblemerchant, Advanced Statistics

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Describe multiple imputation, Multiple imputation : The Monte Carlo techniq...

Multiple imputation : The Monte Carlo technique in which missing values in the data set are replaced by m> 1 simulated versions, where m is usually small (say 3-10). Each of simula

Combine standard deviation, what is the combine standard deviation height f...

what is the combine standard deviation height from the follwing

Factor rotation, Generally the final stage of an exploratory factor analysi...

Generally the final stage of an exploratory factor analysis in which factors derived initially are transformed to build their interpretation simpler. Generally the target of the pr

Wilcoxon''s ranksum test, Wilcoxon's ranksum test is the distribution free...

Wilcoxon's ranksum test is the distribution free method or technique used as an alternative to the Student's t-test for assessing whether two populations have the same location. G

Doubly multivariate data, This term is sometimes used for the data collecte...

This term is sometimes used for the data collected in those longitudinal studies in which more than the single response variable is recorded for each subject on each occasion. For

Treatment allocation ratio, Treatment allocation ratio is the ratio of the...

Treatment allocation ratio is the ratio of the number of subjects allocated to the two treatments in a clinical trial. The equal allocation is most usual in practice, but it might

Frequency distribution, The division of a sample of observations into sever...

The division of a sample of observations into several classes, together with the number of observations in each of them.  It acts as a useful summary of the main features of the da

Bartlett''s test for variances, Bartlett's test for variances : A test for ...

Bartlett's test for variances : A test for equality of the variances of the number (k)of the populations. The test statistic can be given as follows   where s square is an

Parks test, The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedastici...

The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti

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