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The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the multinomial distribution. The continuous variables are supposed to have a multivariate normal distribution in which the means of the variables are permitted to vary from cell to cell of the contingency table, but with the variance-covariance matrix of variables being common to all cells. When there is the single categorical variable with two categories the model becomes that supposed by Fisher's linear discriminant analysis.
Bonferroni correction : A procedure for guarding against the rise in the probability of a type I error when performing the multiple signi?cance tests. To maintain probability of a
In the time series plot and scatter graphs there were many outliers that were clearly visible. These have been removed to identify if they were influential or had high leverage and
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Change point problems : Problems with chronologically ordered data collected over the period during which there is known to have been a change in the underlying data generation cou
Censored observations : An observation xi on some variable of interest is consired to be censored if it is known that xi Li (left-censored)or xi Ui (right-censored) where Li and Ui
The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.
Bioassay : It is an abbreviation of biological assay, which in its classical form includes an experiment conducted on biological material to determine relative potency of test and
How large would the sample need to be if we are to pick a 95% confidence level sample: (i) From a population of 70; (ii) From a population of 450; (iii) From a population of 1000;
Prevented fraction is a measure which can be used to attribute the protection against the disease directly to an intervention. The measure can given by the proportion of disease w
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 Q = ESS/2 >
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