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Unformatted text preview: 16.42845254 to 27.93693208 SUMMARY OUTPUT Regression Statistics Multiple R 0.91 R Square 0.82 Adjusted R Square 0.78 Standard Error 1.57 Observations 6 ANOVA df SS MS Regression 1 46.17 46.17 Residual 4 9.83 2.46 Total 5 56 Coefficients Standard Error t Stat Upper 95% A. What is the dependent variable? Sales B. What is the independent variable? Price D. If a price of $145 is proposed, what is the estimate of the sales? 22.18269231 E. How 'good' is the regression model? R2 = .8245. this means the regression model is okay, but for a reg 160170180190200210220230240250260 5 10 15 20 25 f(x) = 0.09x + 35.85 R² = 0.82 Column C Linear Regression for Column C Price Sales Intercept 35.85 4.39 8.16 48.05 X Variable 10.09 0.024.340.03 ,B6) will be. ression...
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This note was uploaded on 11/22/2010 for the course BUSI 508 taught by Professor Thomas during the Summer '10 term at Columbia College.
 Summer '10
 THOMAS

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