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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.
Weighted least squares is the method of estimation in which the estimates arise from minimizing the weighted sum of squares of the differences between response variable and its pr
Unequal probability sampling is the sampling design in which the different sampling units in the population have different probabilities of being included in sample. The differing
The method of displaying the geographical variability of the disease on maps using different colors, shading, etc. The logic is not new, but the arrival of computers and computer g
Quittingill effect is a problem which occurs most frequently in studies of the smoker cessation where smokers frequently quit smoking following the onset of the disease symptoms
Missing Data - Reasons for screening data In case of any missing data, the researcher needs to conduct tests to ascertain that the pattern of these missing cases is random.
An approach of using the likelihood as the basis of estimation without the requirement to specify a parametric family for data. Empirical likelihood can be viewed as the example of
The Null Hypothesis - H0: There is no first order autocorrelation The Alternative Hypothesis - H1: There is first order autocorrelation Durbin-Watson statistic = 1.98307
Opreation research phase
Confidence interval : A range of the values, calculated from the sample observations which is believed, with the particular probability, to posses the true parameter value. A 95% c
1. define statistical algorithms 2. write the flow charts for statistical algorithms for sums, squares and products. 3. write flow charts for statistical algorithms to generates ra
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