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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.
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
Orthogonal is a term which occurs in several regions of the statistics with different meanings in each case. Most commonly the encountered in the relation to two variables or t
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
Pasture trials is the study in which the pastures are subjected to number of treatments (types of forage, animal management systems, agronomic treatments, and many more)The grazin
i have an assignment for experimental design which is must done by SAS program can you help me also i need to hand in the assignment till thursday shall i send it for you ?
Lagging indicators: The part of a collection of the economic time series designed to give information about the broad swings in measures of the aggregate economic activity known a
Point scoring is an easy distribution free method which can be used for the prediction of a response which is a binary variable from the observations on several explanatory variab
Ignorability : The missing data mechanism is said to be ignorable for likelihood inference if (1) the joint likelihood for the responses of the interest and missing data indicators
Principal components regression analysis is a process often taken in use to overcome the problem of multicollinearity in the regression, when simply deleting a number of the expla
Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have
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