a. Multiple Regression
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Variables |
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|
Model |
Variables Entered |
Variables Removed |
Method |
|
1 |
X17 — Attractive Interior, X15 — X16 – Reasonable Prices, X12 — Friendly |
. |
Enter |
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a. Dependent Variable: X22 — |
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b. All requested variables entered. |
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Model Summary |
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Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
1 |
.456a |
.208 |
.199 |
1.187 |
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a. Predictors: (Constant), X17 — |
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ANOVAa |
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|
Model |
Sum of Squares |
Df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
127.206 |
4 |
31.802 |
22.585 |
.000b |
|
Residual |
484.387 |
344 |
1.408 |
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Total |
611.593 |
348 |
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a. Dependent Variable: X22 — |
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b. Predictors: (Constant), X17 — |
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Coefficientsa |
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|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
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|
B |
Std. Error |
Beta |
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1 |
(Constant) |
1.311 |
.468 |
2.800 |
.005 |
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X12 — Friendly Employees |
.265 |
.058 |
.243 |
4.576 |
.000 |
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X15 — Fresh Food X16 – Reasonable Prices |
.292 .130 |
.060 .055 |
.259 .118 |
4.862 2.341 |
.000 .020 |
|
|
X17 — Attractive Interior |
.152 |
.064 |
.118 |
2.354 |
.019 |
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a. Dependent Variable: X22 — |
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4. Explain fully the concepts of predictive modeling and
regression analysis. Further
demonstrate your critical thinking, communication, and quantitative
reasoning skills. For Santa Fe Grill, what does
the multiple regression reveal about the ability of fresh food and
friendly service to predict customer
satisfaction? Don’t guess.
What are the beta coefficients for each? Explain
fully.
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