Question

In: Statistics and Probability

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


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

Temperature Yield
100 59.63
110 72.28
120 70.98
130 74.35
140 88.23
150 100.28
160 106.41
170 113.01
180 113.71
190 124.07
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 = 0.9839).

1. what is the mean temperature?
155
140
145
130

2. what is the mean yield?
92.2950
91.2125
92.4613
85.324


3. what is the standard deviation of temperature?
22.1631
30.2765
101.5487
900.1573

4. what is the standard deviation of yield?
601.5487
30.2765
491.2040
22.1631
5. The slope of the fitted regression line is closest to:
0.7202
211.4709
78.5291
-12.1340
196.7240
6. The intercept of the fitted regression line is closest to:
196.7240
78.5291
-12.1340
211.4709
7. The yield predicted by the regression model for a temperature of 150 degrees is closest to:
81.492
95.896
92.295
-1819.3798
99.497
8. The residual error for a temperature of 150 degrees is closest to:
-4.3840
-100.28
6
102
4.3840
100.28
9. 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:
0.35274
1/0.35274
would not change
None of the above
10. 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:
0.35274
1/0.35274
would not change
None of the above

Solutions

Expert Solution

1)

Mean = (100 + 110 + 120 + 130 + 140 + 150 + 160 + 170 + 180 + 190)/10
= 1450/10
Mean = 145

2) Mean = (59.63 + 72.28 + 70.98 + 74.35 + 88.23 + 100.28 + 106.41 + 113.01 + 113.71 + 124.07)/10
= 922.95/10
Mean = 92.295

3) Standard Deviation

σ = √(1/10 - 1) x ((100 - 145)2 + (110 - 145)2 + (120 - 145)2 + (130 - 145)2 + (140 - 145)2 + (150 - 145)2 + (160 - 145)2 + (170 - 145)2 + (180 - 145)2 + (190 - 145)2)
= √(1/9) x ((-45)2 + (-35)2 + (-25)2 + (-15)2 + (-5)2 + (5)2 + (15)2 + (25)2 + (35)2 + (45)2)
= √(0.1111) x ((2025) + (1225) + (625) + (225) + (25) + (25) + (225) + (625) + (1225) + (2025))
= √(0.1111) x (8250)
= √(916.575)
= 30.2765

4)
Standard Deviation σ = √(1/10 - 1) x ((59.63 - 92.295)2 + (72.28 - 92.295)2 + (70.98 - 92.295)2 + (74.35 - 92.295)2 + (88.23 - 92.295)2 + (100.28 - 92.295)2 + (106.41 - 92.295)2 + (113.01 - 92.295)2 + (113.71 - 92.295)2 + (124.07 - 92.295)2)
= √(1/9) x ((-32.665)2 + (-20.015)2 + (-21.315)2 + (-17.945)2 + (-4.065)2 + (7.985)2 + (14.115)2 + (20.715)2 + (21.415)2 + (31.775)2)
= √(0.1111) x ((1067.002225) + (400.600225) + (454.329225) + (322.023025) + (16.524225) + (63.760225) + (199.233225) + (429.111225) + (458.602225) + (1009.650625))
= √(0.1111) x (4420.83645)
= √(491.154929595)
= 22.1631

  *** Dear student we answer four sub parts once post remaining separately****


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