Question

Analyze the regression table. Look at each set of results critically and consider how you would interpret the strengths and weaknesses of each model.

Model C: Burglary = f(%Unemploy, Rain, %youngmale)

What are the relationships of some of the results? interpret the strengths and weaknesses of

SUMMARY OUTPUT Regression Statistics Multiple R 0.476608 R Square 0.227155 Adjusted R Square 0.174461 Standard Error 182.3465 Observations 48 653.0 ANOVA of gnificance F 0.0097 Regression Residual Total 3 44 SS MS F 430009.763 143336.6 4.31091 1463010.595 33250.24 18930-20.358 47 State Burglary %Unemploy youngmale Rain ALABAMA 877-8 72 16.7% 583 ARIZONA 732.4 7.7 173% 13.6 ARKANSAS 1,0301 72 16.6% 50.6 CALIFORNIA 605.4 89 16 9% 222 COLORADO 476.1 69 15.5% 159 CONNECTICUT 3585 7.8 16.0% 503 DELAWARE 6623 6.7 165% 45.7 FLORIDA 7105 72 15.6% 545 GEORGIA 8232 82 16.7% 50.7 IDAHO 4119 6.1 16.6% 18.9 ILLINOIS 4521 9 15 9% 392 INDIANA 7.6 16 9% 41.7 IOWA 5135 4.7 17.4% 34 KANSAS 600.4 53 17.6% 28 9 KENTUCKY 596.4 8 16.1% 489 LOUISIANA 8904 6.7 16.7% 60.1 MAINE 488.1 6.7 143% 422 MARYLAND 5389 6.6 15.6% 445 MASSACHUSET 4592 6.7 165% 47.7 MICHIGAN 569.4 8.8 16 9% 328 MINNESOTA 419.0 5 15.2% 273 MISSISSIPPI 835.6 85 17.7% 59 MISSOURI 643.0 6.7 16.4% 422 MONTANA 4003 5.4 16.5% 153 NEBRASKA 4763 3.8 16.8% 23.6 NEVADA 8260 9.6 14.6% 95 NEW HAMPSHIR 373.0 5.1 15.4% 43.4 NEW JERSEY 403.1 82 149% 47.1 NEW MEXICO 1,029 9 69 17.1% 14.6 NEW YORK 2872 7 16 3% 41.8 NORTH CAROLI 921.0 8 16.8% 503 NORTH DAKOTA 405.6 29 203% 17.8 OHIO 7902 7.4 16.0% 39.1 OKLAHOMA 866.1 53 17.1% 365 OREGON 5285 79 15.1% 27.4 PENNSYLVANIA 4073 73 16.1% 429 RHODE ISLAND 5332 93 17.8% 479 SOUTH CAROLI 857.8 7.6 17.2% 49.8 SOUTH DAKOTA 399.1 3.8 16.9% 20.1 TENNESSEE 785.1 7.7 16.0% 542 TEXAS 721.8 63 17.0% 28 9 UTAH 459.6 4.6 19.4% 122 VERMONT 528.7 4.4 17.4% 427 VIRGINIA 3225 5.7 16.1% 443 WASHINGTON 837.0 7 15.5% 384 WEST VIRGINIA 521.7 6.8 15.4% 452 WISCONSIN 424.0 6.7 15.9% 32.6 WYOMING 3355 4.7 16.4% 129 Intercept %Unemploy youngmale Rain Coefficient Standard Error tStot P-value Lower 95% Upper 95% -677.088 499.6174357 -1.35643 0.181883 1684.59 329.214224 13.16108 19.60688693 2.711347 L609521 13.646 92.67616385 4997.625 2651.161638 1.8*507 6066135 -345.44 1034069029 2.576815 1.997214452 1.29.23 0.213711 144826 6.6011986253 Lower 95.0% -1084.591179 13.64599555 -345.4401103 1448056237 Upper 95.0% 379.2147264 9267616385 10340.69129 6.601986253

Answer 1

Date Page 11) Hol if pvalue for each coefficient i less than oros Then only itic Statistically fignificant Otherwise bot Here has pualue co.06 Aignificant others % unempley hot only This CŮ) R25 0.0231= 22.7.4. Burglary due to Variation all predictas fuiy <0.05 is Overall pvalue = o.uoq hence overall model Statistically significent CamScanlher