SUMMARY OUTPUT Regression Statistics Multiple 0.534431614 R Square 0.28561715 Adjusted R Square 0.278252378 Standard Error 5.688982881 Observations 99 ANOVA df Significance F 1.21572 E-08 1 Regression Residual Total SS 1255.146007 3139.359044 4394.505051 MS F 1255.146007 38.78153502 32.36452622 97 98 Intercept Coefficients -18.07211232 0.045216414 Standard Error t Stat P-value 9.54988317 -1.892390933 0.061420901 0.007260786 6.227482237 1.21572 E-08 Lower 95% Upper 95% Lower 95.0% Upper 95.0% -37.02598688 0.881762226 -37.025987 0.88176223 0.030805765 0.059627064 0.03080576 0.05962706 1128 RESIDUAL OUTPUT Observation 1 2 3 4 5 Predicted 25 29.90250343 36.50409994 38.76492067 36.18758504 38.31275652 39.35273405 36.77539843 39.71446537 38.53883859 37.22756257 37.27277899 Residuals -3.902503429 -9.504099942 -10.76492067 -7.187585041 -9.312756521 -10.35273405 -6.775398429 -9.71446537 -6.538838593 -4.227562574 -4.272778988 6 7 8 9 10 11 1 AA Download E 1 (download), and create a piecewise linear regression model to predict traffic flow using a knot value of 40 MPH. True / False: All independent variables in this quadratic model are significant. The coefficient of the vehicle speed term is: (Keep four decimal places) What is the predicted volume if the vehicle speed is 41.5? (Keep one decimal place) SSR = (Enter a whole number) SUMMARY OUTPUT Regression Statistics Multiple 0.534431614 R Square 0.28561715 Adjusted R Square 0.278252378 Standard Error 5.688982881 Observations 99 ANOVA df Significance F 1.21572 E-08 1 Regression Residual Total SS 1255.146007 3139.359044 4394.505051 MS F 1255.146007 38.78153502 32.36452622 97 98 Intercept Coefficients -18.07211232 0.045216414 Standard Error t Stat P-value 9.54988317 -1.892390933 0.061420901 0.007260786 6.227482237 1.21572 E-08 Lower 95% Upper 95% Lower 95.0% Upper 95.0% -37.02598688 0.881762226 -37.025987 0.88176223 0.030805765 0.059627064 0.03080576 0.05962706 1128 RESIDUAL OUTPUT Observation 1 2 3 4 5 Predicted 25 29.90250343 36.50409994 38.76492067 36.18758504 38.31275652 39.35273405 36.77539843 39.71446537 38.53883859 37.22756257 37.27277899 Residuals -3.902503429 -9.504099942 -10.76492067 -7.187585041 -9.312756521 -10.35273405 -6.775398429 -9.71446537 -6.538838593 -4.227562574 -4.272778988 6 7 8 9 10 11 1 AA Download E 1 (download), and create a piecewise linear regression model to predict traffic flow using a knot value of 40 MPH. True / False: All independent variables in this quadratic model are significant. The coefficient of the vehicle speed term is: (Keep four decimal places) What is the predicted volume if the vehicle speed is 41.5? (Keep one decimal place) SSR = (Enter a whole number)
