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Cauchy distribution: The probability distribution, f (x), can be given as follows where α is the position of the parameter (median) and the beta β a scale parameter. Moments and cumulates of distribution do not exist and prevail. The distribution is the unimodal and symmetric is about α with much heavier tails than the normal distribution shown in the figure. The upper and lower quartiles of the distribution are α ± β. Named after the scientist Augustin-Louis Cauchy.
Jelinski Moranda model is t he model of software reliability which supposes that failures occur according to the Poisson process with a rate decreasing as more faults are diagnos
The Null Hypothesis - H0: Model does not fit the data i.e. all slopes are equal to zero β 1 =β 2 =...=β k = 0 The Alternative Hypothesis - H1: Model does fit the data i.e. at
Barnard, George Alfred (1915^2002) : Born in Walthamstow in the east of London, Barnard achieved a scholarship to St. John's College, Cambridge, from where he graduated in the math
The scatter plot of SRES1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plot show that th
Surveys which use lists related with the vital statistics to sample individuals for the further information. For instance, the 1988 National Mortality Follow back Survey sampled de
Multivariate analysis of variance is the procedure for testing equality of the mean vectors of more than two populations for the multivariate response variable. The method is dire
Why Graph theory? It is the branch of mathematics concerned with the properties of sets of points (vertices or nodes) some of which are connected by the lines known as the edges. A
Principal components regression analysis is a process often taken in use to overcome the problem of multicollinearity in the regression, when simply deleting a number of the expla
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
Johnson-Neyman technique: The technique which can be used in the situations where analysis of the covariance is not valid because of the heterogeneity of slopes. With this method
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