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Least significant difference test is an approach to comparing a set of means which controls the family wise error rate at some specific level, let's assume it to be α. The hypothesis or assumption of the equality of the means is tested first by the α-level F-test. If this test is not essential, then the process terminates without making the detailed inferences on pairwise differences; otherwise each pairwise difference is tested by the α-level, Student's.
It is used generally for the matrix which specifies a statistical model for a set of observations. For instance, in a one-way design with the three observations in one group, tw
How do I report the results in the table?
An investor with a stock portfolio sued his broker, claiming that a lack of diversification in his portfolio had led to poor performance. The data, shown below, are the rates of re
Non parametric maximum likelihood (NPML) is a likelihood approach which does not need the specification of the full parametric family for the data. Usually, the non parametric max
Dear Experts, Please note that I''m doing a PhD in Business management under the title: Technology transfer and competitive advantage in Qatar oil and gas companies. It is a quant
There are two periods. You observe that Jack consumes 100 apples in period t = 0, and 120 apples in period t = 1. That is, (c 0 ; c 1 ) = (100; 120) Suppose Jack has the util
Cochrane collaboration : An international network of the individuals committed to preparing , maintaining and disseminating the systematic reviews of the effects of the health care
Incidental parameter problem is a problem which sometimes occurs when the number of parameters increases in the tandem with the number of observations. For instance, models for pa
Mauchly test is a test which a variance-covariance matrix of pair wise differences of responses in the set of longitudinal data is the scalar multiple of identity matrix, a proper
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
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