Question

# BrandA BrandB BrandC 251.6 251.2 263.2 248.6 245.1 262.9 249.4 248 265 242 251.1 254.5 246.5...

 BrandA BrandB BrandC 251.6 251.2 263.2 248.6 245.1 262.9 249.4 248 265 242 251.1 254.5 246.5 260.5 264.3 251.3 250 257 261.8 253.9 262.8 249 244.6 264.4 247.1 254.6 260.6 249.9 248.8 255.9

We can conduct a One-Way ANOVA to compare the true mean distances. However, your instructor wants to you analyze the data using multiple linear regression.

Write the estimated regression equation. Ensure that your regression coefficients are clearly defined and is reported in 3 decimal places.

 SUMMARY OUTPUT Regression Statistics Multiple R 0.303317 R Square 0.092001 Adjusted R Square -0.16743 Standard Error 5.470332 Observations 10 ANOVA df SS MS F Significance F Regression 2 21.22431 10.61215 0.354631 0.713343 Residual 7 209.4717 29.92453 Total 9 230.696 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 142.8814 154.1062 0.927162 0.384696 -221.522 507.2847 BrandB 0.013442 0.385285 0.03489 0.973142 -0.89761 0.924497 BrandC 0.396336 0.471888 0.839895 0.428717 -0.7195 1.512174

estimated regression equation:

y^ = 142.881 + (0.013)Brand B + (0.396)Brand C

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