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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 explanatory variables is not considered correct. Essentially the response variable is regressed on the small number of principal component scores resulting from the principal components analysis of the explanatory variables.
This is an alternative to the Newton-Raphson technique for optimization (finding out the minimum or the maximum) of some function, which includes replacing the matrix of second der
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Continuous variable : The measurement which is not restricted to the particular values except in so far as this is constrained by the accuracy of measuring instrument. General exam
sales per day for a product are as follows: x= 10, 11, 12, 13 (p)= 0.2, 0.4, 0.3, 0.1 obtain mean and variance of daily sale. if the profit is described by the following equation p
Case-cohort study : The research design in epidemiology which involves the sampling of controls at the outset of the study that is to be compared with the cases from the cohort. Th
Modern hotels and certain establishments make use of an electronic door lock system. To open a door an electronic card is inserted into a slot. A green light indicates that the doo
Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
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
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
Suppose that $4 million is available for investment in three projects. The probability distribution of the net present value earned from each project depends on how much is invest
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