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Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is most in agreement with the data configuration. For instance, for the bivariate data, y1,y2, if the quadratic coordinate system is sought, a variable z is defined as given below: with the coefficients being set up so that the variance of z is a maximum amongst all such quadratic functions of y1 and y2.
Blinder Oaxaca method: A method or technique used for assessing the effect of the role of income on racial wealth gap. The method or technique is based on the decomposition of the
Individual differences scaling is a form of multidimensional scaling applicable to the data comprising of a number of proximity matrices from the different sources that is differe
Battery reduction : A common term for reducing the number of variables of the interest in a study for the purposes of study and perhaps later data collection. For instance, an over
Bivariate boxplot : A bivariate analogue of boxplot in which the inner area contains 50%of the data, and a 'fence' helps to identify the potential outliers. Robust methods or techn
Influence statistics: The range of statistics designed to assess the effect or the in?uence of an observation in determining results of the regression analysis. The general approa
Multi-hit model is the model for a toxic response which results from the random occurrence of one or the more fundamental biological events. A response is supposed to be induced o
Mention the characteristics of Statistics. Explain any two applications of Statistics.
Omitted covariates is a term generally found in the connection with regression modelling, where the model has been incompletely specified by not including significant covariates.
The term used in a variety of methods in statistics, but mostly to refer to the categorical variable, with a less number of levels, under examination in an experiment as a possible
Multiple correlation coefficient is the correlation among the observed values of dependent variable in the multiple regression, and the values predicted by estimated regression
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