In: Statistics and Probability
United Oil Company is attempting to develop a reasonably priced unleaded gasoline that will deliver higher gasoline mileages than can be achieved by its current unleaded gasolines. As part of its development process, United Oil wishes to study the effect of two independent variables—x1, amount of gasoline additive RST (0, 1, or 2 units), and x2, amount of gasoline additive XST (0, 1, 2, or 3 units), on gasoline mileage, y. Mileage tests are carried out using equipment that simulates driving under prescribed conditions. The combinations of x1 and x2 used in the experiment, along with the corresponding values of y, are given below.
RST Units (x1) |
XST Units (x2) |
Gas Mileage (y, mpg) |
0 | 0 | 27.73 |
0 | 0 | 28.95 |
0 | 0 | 28.05 |
1 | 0 | 29.25 |
1 | 0 | 30.58 |
2 | 0 | 28.97 |
2 | 0 | 29.18 |
0 | 1 | 32.60 |
0 | 1 | 33.03 |
1 | 1 | 33.85 |
1 | 1 | 34.09 |
0 | 2 | 32.61 |
0 | 2 | 33.81 |
1 | 2 | 34.95 |
1 | 2 | 35.53 |
1 | 2 | 35.63 |
2 | 2 | 33.01 |
2 | 2 | 34.43 |
2 | 2 | 34.14 |
1 | 3 | 33.54 |
2 | 3 | 32.41 |
2 | 3 | 33.81 |
Using the model, y = β0 + β1x1 + β2x12 + β3x2 + β4x22 + ε, calculate the point estimate.
The point estimate can be found by using Excel<Megastats<Regression
Enter x1 and y1 in independent variable and y in dependent variable.
The output is as follows:
Regression Analysis | ||||||
R² | 0.617 | |||||
Adjusted R² | 0.577 | n | 22 | |||
R | 0.785 | k | 2 | |||
Std. Error | 1.635 | Dep. Var. | Y | |||
ANOVA table | ||||||
Source | SS | df | MS | F | p-value | |
Regression | 81.8452 | 2 | 40.9226 | 15.30 | .0001 | |
Residual | 50.8060 | 19 | 2.6740 | |||
Total | 132.6513 | 21 | ||||
Regression output | confidence interval | |||||
variables | coefficients | std. error | t (df=19) | p-value | 95% lower | 95% upper |
Intercept | 29.9803 | |||||
(x1) | -0.1371 | 0.4617 | -0.297 | .7697 | -1.1033 | 0.8291 |
(x2) | 1.8482 | 0.3470 | 5.326 | 3.86E-05 | 1.1218 | 2.5746 |
The Point estimate is 29.9803
Please do the comment in case of any doubt.
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