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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.
You and your team have been hired as strategic consultants by the hugely successful retailer known as “Cutie Pie”. The company sells many products, although one product in particul
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
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
It is the technique used in the clinical trials when it is possible to make an acceptable place before an active treatment but not to make the two active treatments identical. In t
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,
Computer-assisted interviews : A method or technique of interviewing subjects in which the interviewer reads the question from the computer screen instead of the printed page, and
The generalization of the normal distribution used for the characterization of functions. It is known as a Gaussian process because it has Gaussian distributed finite dimensional m
The skewness is a measure of asymmetry and as it is positive at 4.29, it is greater than zero which reveals that the tail extends to the right indicating the distribution to be mor
The approach of controlling the error rate in an exploratory analysis where number of hypotheses are tested, but where the strict control which is provided by multiple comparison p
Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
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