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Biplots: It is the multivariate analogue of the scatter plots, which estimates the multivariate distribution of the sample in a few dimensions, typically two and superimpose on these display representations of the variables on which the samples are measured and observed. The relationships amongst the individual sample points can be simply seen and they can also be related to the values of the measurements, thus making such plots useful for giving the graphical explanation of the data, for detecting patterns, and for giving the results found by more formal methods or techniques of analysis. Figure 16 shows the two-dimensional biplot of a set of multivariate data with 34 observations and 10 variables. Also see principal components analysis and corre- spondence analysis.
Profile plots is a technique of representing the multivariate data graphically. Each of the observation is represented by a diagram comprising of a sequence of equispaced vertical
Multiple correlation coefficient is the correlation among the observed values of dependent variable in the multiple regression, and the values predicted by estimated regression
MAREG is the software package for the analysis of the marginal regression models. The package permits the application of generalized estimating equations and the maximum likelihoo
Laplace distribution : The probability distribution, f(x), given by the following formula Can be derived as the distribution of the difference of two independent random var
Whats the independent variable in the following sentence? -1) In a drug prevention program for boys and girls, will family-participation result in effective drug use reduction?
After graduating from Tech Julia was unable to find regular employment and approached the Director of Athletics at Tech to request that she remain a vendor of the following year.
Human capital model : The model for evaluating the economic implication of the disease in terms of the economic loss of a person succumbing to morbidity or the mortality at some pa
The time series for RESI1, HI1 and COOK1 have appeared again with different outlier values even though the 17 outliers found early were removed.
A rule for computing the number of classes to use while constructing a histogram and can be given by here n is the sample size and ^ γ is the estimate of kurtosis.
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;
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