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Non central distributions is the series of probability distributions each of which is the adaptation of one of the standard sampling distributions like the chi-squared distribution, the F-distribution or Student's t-distribution for distribution of some of the test statistic under the alternative hypothesis or assumptions. Such distributions permit the power of the corresponding hypothesis tests to be calculated. See also non central chi-squared distribution, non central F-distribution and non central t-distribution.
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The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if |t | > t = 1.96
Collapsing categories : A procedure generally applied to contingency tables in which the two or more row or column categories are combined, in number of cases so as to yield the re
Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have
A term commonly encountered in the analysis of the contingency tables. Such type of frequencies are the estimates of the values to be expected under hypothesis of interest. In a tw
A procedure whereby the collection of multiple sample units are combined in their entirety or in part, to form the new sample. One or more succeeding measurements are taken on the
Common cause failures (CCF): Simultaneous failures of the number of components due to a same reason. A reason can be external to the components, or it can be the single failure wh
Occam's razor is an early statement of the parsimony principle, which was given by William of Occam (1280-1349) namely 'entia non sunt multiplicanda praeter necessitatem'; which m
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
i will like to submit my project for you to do on chi-square, ANOVA, and correlation and simple regression. how can we do this?
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