The following data is representative of that reported in anarticle on nitrogen emissions, with x = burner arealiberation rate (MBtu/hr-ft2) and y =NOx emission rate (ppm):
| x | 100 | 125 | 125 | 150 | 150 | 200 | 200 | 250 | 250 | 300 | 300 | 350 | 400 | 400 |
| y | 150 | 130 | 190 | 220 | 190 | 330 | 280 | 400 | 420 | 430 | 400 | 590 | 610 | 680 |
(a) Assuming that the simple linear regression model is valid,obtain the least squares estimate of the true regression line.(Round all numerical values to four decimal places.)
y =____
(b) What is the estimate of expected NOxemission rate when burner area liberation rate equals 225? (Roundyour answer to two decimal places.)
ppm _______
(c) Estimate the amount by which you expect NOxemission rate to change when burner area liberation rate isdecreased by 50. (Round your answer to two decimal places.)
ppm_______
(d) Would you use the estimated regression line to predict emissionrate for a liberation rate of 500? Why or why not?
Yes, the data is perfectly linear, thus lending to accuratepredictions.
Yes, this value is between two existingvalues.   Â
No, this value is too far away from the known values for usefulextrapolation.
No, the data near this point deviates from the overallregression model.
