In: Statistics and Probability
Exercise 12.50 (Algorithmic)}
Consider the following data for two variables, x and
y.
| xi | 135 | 110 | 135 | 150 | 175 | 160 | 125 | 
| yi | 145 | 105 | 120 | 120 | 135 | 130 | 115 | 
a. Compute the standardized residuals for these data.
| Observation 1 | |
| Observation 2 | |
| Observation 3 | |
| Observation 4 | |
| Observation 5 | |
| Observation 6 | |
| Observation 7 | 
I got 23.13 for the first one and it was wrong
For the give data using Regression in Excel we get output as
| SUMMARY OUTPUT | ||||||
| Regression Statistics | ||||||
| Multiple R | 0.615426681 | |||||
| R Square | 0.37875 | |||||
| Adjusted R Square | 0.2545 | |||||
| Standard Error | 11.53798076 | |||||
| Observations | 7 | |||||
| ANOVA | ||||||
| df | SS | MS | F | Significance F | ||
| Regression | 1 | 405.8035714 | 405.8036 | 3.04829 | 0.141260351 | |
| Residual | 5 | 665.625 | 133.125 | |||
| Total | 6 | 1071.428571 | ||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
| Intercept | 71.25 | 30.68811692 | 2.321746 | 0.067906 | -7.636315883 | 150.1363159 | 
| X | 0.375 | 0.214784603 | 1.745935 | 0.14126 | -0.177121399 | 0.927121399 | 
| RESIDUAL OUTPUT | ||
| Observation | Predicted Y | Residuals | 
| 1 | 121.875 | 23.125 | 
| 2 | 112.5 | -7.5 | 
| 3 | 121.875 | -1.875 | 
| 4 | 127.5 | -7.5 | 
| 5 | 136.875 | -1.875 | 
| 6 | 131.25 | -1.25 | 
| 7 | 118.125 | -3.125 |