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The approach of controlling the error rate in an exploratory analysis where number of hypotheses are tested, but where the strict control which is provided by multiple comparison procedures controlling the family wise error rate is not needed.
Assume that the m hypotheses are to be tested, of which m0 relate to cases where the null hypothesis is true and the remaining m-m0 relate to the cases where alternative hypo- thesis is true. The FDR is defined as expected proportion of the incorrectly rejected null hypotheses. Explicitly FDR is given by the formula written below where V represents several true null hypotheses which are rejected and R is the total number of the rejected hypotheses. Procedures which exercise control over the FDR guarantee that the FDR < α, for some fixed value of α.
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
2 jobs n machines,graphical method,how to determine which job should proceed first on each machine
The GRE has a combined verbal and quantitative mean of 1000 and a standard deviation of 200.
ain why the simulated result doesn''t have to be exact as the theoretical calculation
This process of estimating from a data set those values lying beyond range of the data. In the regression analysis, for instance, a value of the response variable might be estimate
Assume that a population is normally distributed with a mean of 100 and a standard deviation of 15. Would it be unusual for the mean of a sample of 20 to be 115 or more?
ACC – A pioneer in the Indian cement industry Associated Cement Companies Ltd. (ACC) came into existence in 1936, after the merger of 10 companies belonging to four important bus
Odds ratio is the ratio of the odds for the binary variable in two groups of the subjects, such as, males and females. If the two possible states of variable are labeled as 'succe
can you help specify the model for an event study and to interpret the results/
This is the theorem which states that if the error terms in a multiple regression have the same variance and are not corrected, then the estimators of the parameters in the model p
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