In: Statistics and Probability
| Student | First Test Grade | Second Test Grade |
| 1 | 81 | 79 |
| 2 | 55 | 64 |
| 3 | 52 | 61 |
| 4 | 81 | 74 |
| 5 | 50 | 65 |
| 6 | 70 | 71 |
| 7 | 43 | 64 |
| 8 | 43 | 58 |
| 9 | 77 | 75 |
| 10 | 97 | 88 |
| 11 | 48 | 64 |
| 12 | 48 | 68 |
| 13 | 70 | 70 |
| 14 | 75 | 71 |
| 15 | 77 | 72 |
| 16 | 76 | 73 |
| 17 | 85 | 80 |
| 18 | 91 | 85 |
| 19 | 70 | 75 |
| 20 | 69 | 77 |
| 21 | 40 | 57 |
Step 1:
Enter a negative estimate as a negative number in the regression model. round your answers to 4 decimal places, if necassary
yi=________+(_____________)xi
Step 2: Interpret the coefficient of the first test grade in the model.
Scatter plot::

Y = 40.8865 + 0.4523 X
| R Square | 0.870029726 |
Correlation cofficieent:
r = 0.9328
| SUMMARY OUTPUT | ||||||||
| Regression Statistics | ||||||||
| Multiple R | 0.93275384 | |||||||
| R Square | 0.870029726 | |||||||
| Adjusted R Square | 0.863189186 | |||||||
| Standard Error | 3.06129724 | |||||||
| Observations | 21 | |||||||
| ANOVA | ||||||||
| df | SS | MS | F | Significance F | ||||
| Regression | 1 | 1191.941 | 1191.941 | 127.1873 | 7.34E-10 | |||
| Residual | 19 | 178.0593 | 9.371541 | |||||
| Total | 20 | 1370 | ||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
| Intercept | 40.88645282 | 2.752473 | 14.85444 | 6.53E-12 | 35.12546 | 46.64745 | 35.12546 | 46.64745 |
| X Variable 1 | 0.452349421 | 0.04011 | 11.27773 | 7.34E-10 | 0.368398 | 0.536301 | 0.368398 | 0.536301 |