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Andrews ‘Plots
A graphical display of multivariate data in which an observation, x0 = [x1, x2, . . . , xq] is represented can be represented in the form of function
A set of the multivariate observations is then displayed as the collection of these kind of plots and it can be shown that those functions which remain close together for all values of t correspond to the observations which are close to one another in the terms of their Euclidean distance. This property states that such plots can often be used to detect groups of similar observations and identify outliers in multivariate data both. The example given in the Fig drawn below consists of plots for the sample of 30 observations each of which having five variable values.
The plot signifies the presence of three groups in the data. These type of plots can cope only with a reasonable number of observations before becoming very complicated to unravel.
Estimate a linear probability model: Consider the multiple regression model: y = β 0 +β 1 x 1 +.....+β k x k +u Suppose that assumptions MLR.1-MLR4 hold, but not assump
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show that (N,/) IS NOT A SEMI GROUP
Analysis of covariance (ANCOVA) It is initially used for an expansion of the analysis of variance which permits to the possible effects of continuous concomitant variables (suc
Histogram: It is generally used for charting continuous frequency distribution. In histogram, data are plotted as a series of rectangle one over the other. Class intervals
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Quota sampling Under this method enumerators shall select the respondents in place of those not available, as per the quota fixed according to guide lines provided to them.
Difference between Correlation and Regression Analysis 1. Degree and Nature of Relationship: Coefficient of correlation measures the degree of covariance between two vari
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