RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM

This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program includes a rule for determining which of up to fifty independent variables are statistically significant, and calculates the coefficients of the least square...

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description This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program includes a rule for determining which of up to fifty independent variables are statistically significant, and calculates the coefficients of the least squares linear regression equations in which only the significant variables appear. The output includes the means, standard deviations, and correlation coefficients of the input variables, the regression coefficients, their standard errors and correlations, and an anal/is-ofvariance table. The available options include fixed point output, choice of four F tables, flexible input format, llllliiisting of the input variables and the residuals, the use of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)
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The program includes a rule for determining which of up to fifty independent variables are statistically significant, and calculates the coefficients of the least squares linear regression equations in which only the significant variables appear. The output includes the means, standard deviations, and correlation coefficients of the input variables, the regression coefficients, their standard errors and correlations, and an anal/is-ofvariance table. The available options include fixed point output, choice of four F tables, flexible input format, llllliiisting of the input variables and the residuals, the use of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. 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The program includes a rule for determining which of up to fifty independent variables are statistically significant, and calculates the coefficients of the least squares linear regression equations in which only the significant variables appear. The output includes the means, standard deviations, and correlation coefficients of the input variables, the regression coefficients, their standard errors and correlations, and an anal/is-ofvariance table. The available options include fixed point output, choice of four F tables, flexible input format, llllliiisting of the input variables and the residuals, the use of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. 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The program includes a rule for determining which of up to fifty independent variables are statistically significant, and calculates the coefficients of the least squares linear regression equations in which only the significant variables appear. The output includes the means, standard deviations, and correlation coefficients of the input variables, the regression coefficients, their standard errors and correlations, and an anal/is-ofvariance table. The available options include fixed point output, choice of four F tables, flexible input format, llllliiisting of the input variables and the residuals, the use of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)</abstract><oa>free_for_read</oa></addata></record>
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subjects ANALYSIS OF VARIANCE
COMPUTER PROGRAMMING
LEAST SQUARES METHOD
MATRICES(MATHEMATICS)
MULTIPLE REGRESSION ANALYSIS
STATISTICAL ANALYSIS
title RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM
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