A chemical engineer is investigating the effect of process operating temperature

Question

A chemical engineer is investigating the effect of process operating temperature on product yield.The study results in the following data:

190

125.30

Correlation Coefficient: r=0.9598

1. The slope of the fitted regression line is closest to:
a. 213.3626
b. -13.4560
c. 199.5780
d. 0.7346
e. 76.6374

2. The intercept of the fitted regression line is closest to:
a. -13.4560
b. 213.3626
c. 0.7346
d. 199.5780

3. The yield predicted by the regression model for a temperature of 150 degrees is closest to:
a. 96.734
b. -2017.6654
c. 100.407
d. 82.042
e. 93.061

4. The residual error for a temperature of 150 degrees is closest to:
a. -89.04
b. -7.6940
c. 89.04
d. 7.6940
e. 18446744073709551611
f. 91

5. 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:
a. 0.35274
b. 1/0.35274
c. would not change
d. None of the above

6. 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:
a. 0.35274
b. 1/0.35274
c. would not change
d. None of the above

Temperature Yield 100 61.68 110 59.30 120 78.41 130 91.18 140 83.21 150 89.04 160 114.07 170 113.41 180 115.01

190

125.30

Explanation / Answer

1) D .Slope = r * Sy / Sx = 0.9598 *23.17/30.27 = 0.7376 .

2)B

Average Y = 93.06, Average X = 145

93.06= 0.7376* 145+b So, b = -13.45

3) A

Yield = 0.7376*150 -13.45 = 96.73

4) B

Residual Error = Actual -Predicted = 89.04 96.73 = -7.6940

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