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     <td>Within Normal Hours</td>
     <td>Within Normal Hours</td>
     <td> <div align="center">12</div></td>
     <td> <div align="center">12</div></td>
The results are:
Difference = p (1) - p (2)
Estimate for difference:  0.170035
95% CI for difference:  (0.0346494, 0.305420)
Test for difference = 0 (vs not = 0):  Z = 2.37  P-Value = 0.018
Fisher's exact test: P-Value = 0.026
Discussion
1. Why is the Fisher exact test P-Value (0.026) to be preferred to the other P-Value mentioned (0.018)?
2. The Wall Street Journal mentioned several caveats “making it difficult to determine the underlying reasons for the after-hours patients’ poor outcomes.”  List a few practical significance hedges to the statistically significant result.
    <td> <div align="center">70</div></td>
    <td> <div align="center">.1714</div></td>
  </tr>
</table>
</table>

Revision as of 14:22, 13 September 2009

Breaking News

The Wall Street Journal of September 8, 2009 reports on a study in the Journal of Bone and Joint Surgery: “The researchers compared the outcomes of patients who underwent surgery between 6 a.m. and 4 p.m. for fractures of the femur or tibia to those who had comparable surgeries for similar fractures outside those normal hours.”

Sample

Reoperations

Needed

Sample Size
Sample Proportion
Outside Normal Hours
28
82

.3415

Within Normal Hours
12