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Agency revenues. An economic consultant was retained by a large employment agency in a metropolitan area to develop a regression model for predicting monthly agency revenues ( y ). She decided that three economic indicators for the area were potentially useful as independent variables, namely, average weekly overtime hours of production workers in manufacturing ( 1 x ), number of job vacancies in manufacturing ( 2 x ), and index of help wanted advertising in newspapers ( 3 x ). Monthly observations on agency revenues and the three independent variables were obtained for the past 25 months. The ANOVA table for the model is as follows:
The consultant decided to screen the independent variables to determine the best set for predicting agency revenues. The regression sums of squares for all possible regression models were found to be as follows:
(a) Determine the subset of variables that is selected as best by the forward selection procedure using F0* = 4.2 (to-add-variable). Show your steps. (b) Determine the subset of variables that is selected as best by the backward elimination procedure using F0** = 4.1 (to-delete-variable). Show your steps.
NOTE: ( t0** ) 2 = F0** (c) Determine the subset of variables that is selected as best by the stepwise regression procedure using F0* = 4.2 (to-add) and F0** = 4.1 (to-delete). Show your steps.
The file Midterm Data.xls has a tab labeled "Many vs. S&P" which presents historical price data for several assets, a volatility condition (VIDX = 1 if the NYSE volatility is grea
Complete the multiple regression model using Y and your combined X variables. State the equation. Next, make sure that you evaluate overall model performance with the Anova table
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Your employer, Quick Hit Agency (QHA), is a debt collections agency. The company specializes in collecting small accounts. QHA does not deal in large accounts and does not take on
Correlation Analysis Correlation Analysis is performed to measure the degree of association between two variables. The measure is called coefficient of correlation. The coeffic
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Correspondence Analysis (CA) is a generalization of PCA to contingency tables. The factors of correspondence analysis give an orthogonal decomposi:ion of the Chi- square associated
how can we use measurement error method with eight responses variables (we do not have explanatory variable in the data )?.the data analyse 521 leaves ..
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