A multiple regression analysis produced the following tables. SUMMARY OUTPUT Reg

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A multiple regression analysis produced the following tables. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Squa Standard Error Observations 0.978724022 0.957900711 0.952287472 67.67055418 18 ANOVA MS Significance F Regression Residual Total 1562918.941 781459.5 170.6503 68689.55855 4579.304 4.80907E-11 15 17 1631608.5 Coefficients Standard Error t Stat P-value 1959.709718 -0.469657287 2.163344882 Using a 0.01 to test the model, these results indicate that Intercept X1 X2 306.4905312 6.39403 1.21E-05 0.264557168 -152 0.096144 0.278361425 -77171 1.23E-06 at least one of the regression variables is a significant predictor of y none of the regression variables are significant predictors ofy the y intercept in this model is the best predictor variable y cannot be sufficiently predicted using these data

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