<p>The following is the analysis from excel using the miles, HYP and index values. Note the Coefficient value for HYP. The quantification of the “Blood Sport” gives an index value of -56. </p>
<p>SUMMARY OUTPUT </p>
<p>Regression Statistics<br>
Multiple R 0.833108<br>
R Square 0.694069<br>
Adjusted R Square 0.632882<br>
Standard Error 29.25909<br>
Observations 13 </p>
<p>ANOVA<br>
df SS MS F Significance F
Regression 2 19422.29 9711.143 11.34354 0.00268
Residual 10 8560.945 856.0945<br>
Total 12 27983.23 </p>
<pre><code>Coefficients Standard Error t Stat P-value Lower 95%
</code></pre>
<p>Intercept 162.1198 16.49372 9.829186 1.86E-06 125.3695
miles 0.095707 0.020385 4.69492 0.000848 0.050286
hyp -56.6546 18.73918 -3.02333 0.012822 -98.4081</p>
<p>RESIDUAL OUTPUT </p>
<p>Observation Predicted index Residuals Standard Residuals<br>
1 141.1639 19.83605 0.742651 chic<br>
2 197.8186 27.18143 1.017659 n w
3 192.2676 -40.2676 -1.5076 vandy<br>
4 217.1554 -9.15539 -0.34277 harv<br>
5 196.1955 30.80447 1.153303 price<br>
6 249.6918 52.30818 1.958391 cornell
7 216.1943 -12.1943 -0.45655 rice<br>
8 260.415 -11.415 -0.42737 stan<br>
9 303.0007 -3.00068 -0.11234 usc
10 217.1554 -37.1554 -1.39108 MIT
11 206.9147 7.085269 0.265269 yale<br>
12 174.9446 -15.9446 -0.59696 wash u<br>
13 203.0825 -8.08246 -0.3026 n d </p>
<p>Note Vanderbilt’s high negative residual.</p>
<p>Time to watch football- I’ll be back later.</p>