1- Solve for the missing values (yellow highlighted)in the following table and test for the global usefulness of the model using a=0.01. Identify the null and the alternative hypotheses and the test statistic.< SUMMARY OUTPUT Regression Statistics Multiple Re R Square Adjusted R Square e Standard Errore Observations ANOVA SS MS Regression 197910754.8 Residual 562923.1651 Total 29 210857987.6 Coefficients Standard Errore t State Intercept 496.6700458 3409.504939 0.145672188 FARE -204.3225415 -0.415423264 GASPRICE 3316.072656 0.47013468 INCOME -0.093980627 0.102729232 -0.914838208 POPO 0.29637716 e DENSITY 0.056142541 0.0892985 0.628706423 LANDAREA -1.744165638 2.234037353 -0.780723579 e df P-value (3 Lower 95% Upper 95% -6556.428293 7549.768385 -1221.7749 813.1298174 -5300.81818 8418.819692 -0.306492236 0.118530982 1.19691454 2.423120274 -0.128585481 0.240870562 -6.365624011 2.877292734 tttttttt R

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