In: Statistics and Probability
            A chemical engineer is investigating the effect of process
operating temperature on product yield. The study...
                
            A chemical engineer is investigating the effect of process
operating temperature on product yield. The study results in the
following data:
| Temperature | 
 | 
Yield | 
| 100 | 
 | 
56.17 | 
| 110 | 
 | 
72.28 | 
| 120 | 
 | 
75.68 | 
| 130 | 
 | 
73.30 | 
| 140 | 
 | 
90.95 | 
| 150 | 
 | 
90.21 | 
| 160 | 
 | 
103.68 | 
| 170 | 
 | 
114.28 | 
| 180 | 
 | 
123.66 | 
| 190 | 
 | 
 130.66 
 | 
You can use Minitab to answer the following questions.
However, you should be able to calculate the slope and intercept of
the least squares regression model by hand, which requires only the
means and standard deviations of X and Y, and the correlation
coefficient (here r = 0.9829).
- The intercept of the fitted regression line is closest to:
 
- The yield predicted by the regression model for a temperature
of 150 degrees is closest to:
 
- The residual error for a temperature of 150 degrees is closest
to:
 
- If the yield were measured in ounces instead of grams (note
that 1 gram is 0.35274 ounces), the slope would change by a factor
of:
 
- If the yield were measured in ounces instead of grams (note
that 1 gram is 0.35274 ounces), the correlation coefficient would
increase by a factor of: