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The method of summarizing the large amounts of data by forming the frequency distributions, scatter diagrams, histograms, etc., and calculating statistics like means variances and correlation coefficients. The term is also used when obtaining the low-dimensional representation of multivariate data by methods such as principal components analysis and the factor analysis.
Projection pursuit is a procedure for attaning a low-dimensional (usually two-dimensional) representation of the multivariate data, which will be particularly useful in revealing
The values assigned to factors for the individual sample units in a factor analysis. The most common approach is "regression method". When the factors are seen as the random variab
A radically different approach of dealing with the uncertainty than the traditional probabilistic and the statistical methods. The necessary feature of the fuzzy set is a membershi
Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights
Inliers is the term used for the observations most likely to be subject to error in situations where the dichotomy is developed by making a ‘cut’ on an ordered scale, and where th
Regression dilution is the term which is applied when a covariate in the model cannot be measured directly and instead of that a related observed value must be used in analysis. I
Different approaches to the study of early indian history
Geographical analysis machine is the procedure designed to detect the clusters of rare diseases in a particular area. Circles of fixed radii are created at each point of the squar
Canonical correlation analysis : A process of analysis for investigating the relationship between the two groups of variables, by ?nding the linear functions of one of the sets of
Obuchowski and Rockette method is an alternative to the Dorfman-Berbaum-Metz technique for analyzing multiple reader receiver operating curve data. Instead of the modelling the ja
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