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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.
moving and semi average method graphical reprsentation
difference between histogram and historigram
The contingency tables in which the row and column both the categories follow a natural order. An instance for this might be, drug toxicity ranging from mild to severe, against the
what is operational gaining
Mantel Haenszel estimator is an estimator of assumed common odds ratio in the series of two-by-two contingency tables arising from the different populations, for instance, occ
Chi-squared distribution : It is the probability distribution, f (x), of the random variable de?ned as the sum of squares of the number (v) of independent standard normal variables
1) Has smartphones affected the consumer behavior? If so How ? And how is it going to change in future? 2) Forecasting of Mobile market (Time series analysis) 3) Comparison of fou
Hanging rootogram is he diagram comparing the observed rootogram with the ?tted curve, in which dissimilarities between the two are displayed in relation to the horizontal axis,
Over dispersion is the phenomenon which occurs when empirical variance in the data exceeds the nominal variance under some supposed model. Most often encountered when the modeling
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
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