Homework Answers
Answer:
Given data,
The total expenses of a hospital are related to many factors. Two
of these factors are the number of beds in the hospital and the
number of admissions.
| Regression Analysis | ||||
|
R2 Adjusted R2 R std.error |
0.975 0.970 0.987 8.369 |
n k Dep.var |
14 2 Total Express |
|
| ANOVA table | |||||
| Source | ss | df | MS | F | P-Value |
| Regression | 29,901,3414 | 2 | 14,950.6707 | 213.48 | 158E.09 |
| Residual | 770,3729 | 11 | 70.0339 | ||
| Total | 30,6717143 | 13 |
| Regression output | Confidence Interval | |||||
| Variables | Coefficient | std.error | t(df=11) | P-value | 95% lower | 95% upper |
| Intercept | 0.6539 | 3.7565 | 0.174 | .8650 | -7.6141 | 8.9219 |
| Number of beds | 0.0231 | 0.0465 | 0.511 | .6196 | -0.0763 | 0.1224 |
| Admissions | 0.6230 | 0.0950 | 6.557 | 4.10E-05 | 0.4139 | 0.8321 |
The estimated regression line is
Total expenses=0.6539+0.0231*Number of beds+0.6230*Admissions.
95% of variation in total expenses is explained by the model
| Regression Analysis | ||||
| r2 | 0.974 | n | 14 | |
| r | 0.987 | k | 1 | |
| std.error | 8.107 | Dep.Var | Total Expenses |
| ANOVA table | |||||
| Source | ss | df | MS | F | p-value |
| Regression | 29,883.0730 | 1 | 29,883.0730 | 454.70 | 659E.11 |
| Residual | 788.6412 | 12 | 65,7201 | ||
| Total | 30,671.7143 | 13 |
| Regression Output | Confidence Interval | |||||
| Variables | coefficients | std.error | t(df=12) | p-value | 95% lower | 95% Upper |
| Intercept | 1,5181 | 3.2489 | 0.467 | .6487 | -5.5608 | 8.5969 |
| Admissions | 0.6686 | 0.0314 | 21.324 | 6.59E-11 | 0.6003 | 0.7369 |
The best regression model is
Total expenses=1.5181+0.6686*Admissions
97.4% of variation in total expenses is explained by this model.
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