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Homoscedasticity - Reasons for Screening Data
Homoscedasticity is the assumption that the variability in scores for a continuous variable is roughly the same at all values of another continuous variable.
1. In the bivariate case, this is referred to as homogeneity of variances. Usually the Leven's test is the tool to assess the homogeneity of variances. This test is used to assess the hypothesis that assumes samples of observations come from populations from the same variances. Therefore rejecting it would imply heterogeneity of variances.
2. In multivariate analysis this is referred to Homoscedasticity. Homoscedasticity is related to the assumption of multivariate normality. Therefore bivariate scatterplots could be used to detect heteroscedasticity. Heteroscedastic relationship could also mean that one of the variables in the group of variables to be analyzed has a relationship with the transformation of the other variable.
Bayesian network : It is essentially an expert system in which the uncertainty is dealt with using the conditional probabilities and Bayes' Theorem. Formally such type of network c
A two-step distillation and mixing process is shown in the figure. The system operates at steady-state conditions and there are no chemical reactions. The known flow rates and comp
Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of
Bootstrap : The data-based simulation method/technique for the statistical inference which can be used to study the variability of the estimated characteristics of the probability
Respondent-driven sampling (RDS ): The form of snowball sampling which starts with the recruitment of the small number of people in the target population to serve as the seeds. Aft
Formal graphical representation of the "causal diagrams" or the "path diagrams" where the relationships are directed but acyclic (that is no feedback relations allowed). Plays an
#how to analyse data
Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the
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Captures recapture sampling : Another approach to a census for estimating the size of population, which operates by sampling the population number of times, identifying the individ
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