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This is the powerful visualization tool for studying how the response relies on an explanatory variable given the values of other explanatory variables. The plot comprises of a number of panels one of which shows the values of the particular explanatory variable divided into the number of intervals, while the others show the scatter plots of the response variable and an another explanatory variable corre- sponding to each and every interval in the given panel. The plot is checked by moving from left to right through intervals in the given panel, while at the same time moving from left to right and then from the bottom to top through the dependence of the panels. The example shown
In the figure involves the relationship between packed cell volume and white blood cell count for the given haemoglobin concentration.
A test for equality of the variances of the two populations having normal distributions, based on the ratio of the variances of the sample of observations taken from each. Most fre
Attack rate : This term frequently used for the incidence of the disease or condition in the particular group, or during a limited interval of time, or under the special circumstan
Higher criticism is a multiple-comparison test concept arising from the situation where there are number of independent tests of significance and interest lies in the rejecting jo
Hot deck is a method broadly used in surveys for imputing the missing values. In its easiest form the method includes sampling with replacement m values from the sample respondent
What is the EM?
distinguish the historigram and histogram
Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
Literature controls : The patients with the disease of interest who have received, in the past, one of two treatments under the investigation, and for whom the results have been pu
Principal factor analysis is the method of factor analysis which is basically equivalent to a principal components analysis performed on reduced covariance matrix attained by repl
The Null Hypothesis - H0: There is no first order autocorrelation The Alternative Hypothesis - H1: There is first order autocorrelation Durbin-Watson statistic = 1.98307
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