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Submitted By nedaniel

Words 1030

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Words 1030

Pages 5

Course Project

Ebenezer Newman and Mark Cherry

* NE (Northeast)

1: Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut, New York, Pennsylvania, New Jersey

0: Others * MW (Midwest)

1: Wisconsin, Michigan, Illinois, Indiana, Ohio, Missouri, North Dakota, South Dakota, Nebraska, Kansas, Minnesota, Iowa

0: Others * WEST (West)

1: Idaho, Montana, Wyoming, Nevada, Utah, Colorado, Arizona, New Mexico, Alaska, Washington, Oregon, California, Hawaii

0: Others * Region 3 (South) Delaware, Maryland, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida, Kentucky, Tennessee, Mississippi, Alabama, Oklahoma, Texas, Arkansas, Louisiana

Scatter plots

Get the scatter plots for each variable against the crime rate

VIF

From the result we see that there is no Multicorinality

Predictor Coef SE Coef T P VIF

Constant -340 1101 -0.31 0.759

NEAST -304.9 508.9 -0.60 0.553 3.307

MID-WEST -164.5 475.2 -0.35 0.731 3.564

WEST 351.6 588.9 0.60 0.554 5.773

PINCOME -0.01055 0.07966 -0.13 0.895 4.154

DROPOUT 70.66 26.61 2.66 0.011 2.975

PUBAID -76.43 86.78 -0.88 0.384 2.305

DENSITY -1.6666 0.9109 -1.83 0.075 3.760

KIDS 0.851 1.801 0.47 0.639 3.959

PRECIP 7.69 13.85 0.56 0.582 3.328

UNEMPLOY -93.30 89.99 -1.04 0.306 2.503

URBAN 60.07 12.46 4.82 0.000 2.791

1 X | | | | | | | | | | | | | | p-value | | | | NEAST | 0.553 | | | | | MID-WEST | 0.731 | | | | | WEST | 0.554 | | | | | PINCOME | 0.895 | | | | | DROPOUT | 0.011 | | | | | PUBAID | 0.384 | | | | | DENSITY | 0.075 | | | | | KIDS | 0.639 | | | | | PRECIP | 0.582 | | | | | UNEMPLOY | 0.306 | | | | | URBAN | 0 | | | | | | | | | | | 2 X | | URBAN | | | | NEAST | 0.036 | 0 | | | | MID-WEST | 0.042 | 0 | | | | WEST | 0.038 | 0 | | | | PINCOME | 0.22 | 0 | | | | DROPOUT | 0.002 | 0 | | | | PUBAID | 0.572 | 0 | | | | DENSITY | 0.003 | 0 | | | | KIDS | 0.175 | 0 | | | | PRECIP | 0.825 | 0 | | | | UNEMPLOY | 0.163 | 0 | | | | | | | | | | 3 X | | URBAN | DROPOUT | | | NEAST | 0.036 | 0 | 0.002 | | | MID-WEST | 0.482 | 0 | 0.019 | | | WEST | 0.004 | 0 | 0 | | | PINCOME | 0.354 | 0 | 0.004 | | | PUBAID | 0.025 | 0 | 0 | | | DENSITY | 0.001 | 0 | 0 | | | KIDS | 0.887 | 0 | 0.007 | | | PRECIP | 0.065 | 0 | 0 | | | UNEMPLOY | 0.819 | 0 | 0.007 | | | | | | | | | 4 X | | URBAN | DROPOUT | DENSITY | | NEAST | 0.83 | 0 | 0.001 | 0.007 | | MID-WEST | 0.18 | 0 | 0.011 | 0 | | WEST | 0.175 | 0 | 0.001 | 0.021 | | PINCOME | 0.369 | 0 | 0 | 0.001 | | PUBAID | 0.07 | 0 | 0 | 0.002 | | KIDS | 0.502 | 0 | 0.001 | 0.001 | | PRECIP | 0.749 | 0 | 0.003 | 0.004 | | UNEMPLOY | 0.14 | 0 | 0 | 0 | | | | | | | | 5 X | | URBAN | DROPOUT | DENSITY | PUBAID | NEAST | 0.95 | 0 | 0 | 0.018 | 0.075 | MID-WEST | 0.387 | 0 | 0.004 | 0.001 | 0.137 | WEST | 0.312 | 0 | 0 | 0.024 | 0.118 | PINCOME | 0.591 | 0 | 0 | 0.004 | 0.099 | KIDS | 0.321 | 0 | 0 | 0.001 | 0.052 | PRECIP | 0.972 | 0 | 0.001 | 0.005 | 0.077 | UNEMPLOY | 0.418 | 0 | 0 | 0.002 | 0.186 | | | | | | | | | | | | | | | | | | | | | | | | | 6 X | | URBAN | DROPOUT | DENSITY | PUBAID | KIDS | | | | NEAST | 0.683 | 0 | 0 | 0.03 | 0.05 | 0.289 | | | | MID-WEST | 0.435 | 0 | 0.003 | 0.001 | 0.106 | 0.36 | | | | WEST | 0.443 | 0 | 0 | 0.018 | 0.095 | 0.458 | | | | PINCOME | 0.906 | 0 | 0 | 0.007 | 0.069 | 0.406 | | | | PRECIP | 0.931 | 0 | 0.001 | 0.004 | 0.058 | 0.325 | | | | UNEMPLOY | 0.574 | 0 | 0 | 0.002 | 0.141 | 0.425 | | | | | | | | | | | | | | 7 X | | URBAN | DROPOUT | DENSITY | PUBAID | KIDS | MID-WEST | | | NEAST | 0.498 | 0 | 0.003 | 0.036 | 0.099 | 0.267 | 0.345 | | | WEST | 0.722 | 0 | 0.004 | 0.03 | 0.118 | 0.44 | 0.7 | | | PINCOME | 0.979 | 0 | 0.005 | 0.006 | 0.148 | 0.501 | 0.445 | | | PRECIP | 0.837 | 0 | 0.001 | 0.003 | 0.107 | 0.361 | 0.427 | | | UNEMPLOY | 0.506 | 0 | 0.003 | 0.002 | 0.264 | 0.491 | 0.393 | | | | | | | | | | | | | 8 X | | URBAN | DROPOUT | DENSITY | PUBAID | KIDS | MID-WEST | NEAST | | WEST | 0.919 | 0 | 0.006 | 0.07 | 0.109 | 0.341 | 0.543 | 0.563 | | PINCOME | 0.992 | 0 | 0.006 | 0.064 | 0.138 | 0.39 | 0.357 | 0.504 | | PRECIP | 0.828 | 0 | 0.012 | 0.045 | 0.1 | 0.269 | 0.34 | 0.501 | | UNEMPLOY | 0.375 | 0 | 0.003 | 0.026 | 0.293 | 0.333 | 0.269 | 0.37 | | | | | | | | | | | | | | | | | | | | | | | | | | | | 9 X | | URBAN | DROPOUT | DENSITY | PUBAID | KIDS | MID-WEST | NEAST | UNEMPLOY | WEST | 0.715 | 0 | 0.004 | 0.058 | 0.359 | 0.496 | 0.568 | 0.468 | 0.345 | PINCOME | 0.905 | 0 | 0.005 | 0.05 | 0.307 | 0.404 | 0.286 | 0.373 | 0.376 | PRECIP | 0.825 | 0 | 0.011 | 0.032 | 0.29 | 0.334 | 0.266 | 0.373 | 0.38 | | | | | | | | | | | | | | | | |

S = 744.747 R-Sq = 70.2% R-Sq(adj) = 63.5%

The regression equation is

CRIMES = - 306 + 60.8 URBAN + 70.7 DROPOUT - 1.76 DENSITY - 80.3 PUBAID + 1.17 KIDS - 360 MID-WEST - 412 NEAST - 72.9 UNEMPLOY

If we drop the variable UNEMPLOYMENT

The regression equation is

CRIMES = - 576 + 60.2 URBAN + 69.4 DROPOUT - 1.59 DENSITY - 112 PUBAID + 1.32 KIDS - 299 MID-WEST - 297 NEAST

No VIF is above 10 in the final model

Predictor Coef SE Coef T P VIF

Constant -306.3 838.6 -0.37 0.717

NEAST -411.8 454.3 -0.91 0.370 2.812

MID-WEST -360.1 321.1 -1.12 0.269 1.736

DROPOUT 70.69 22.36 3.16 0.003 2.240

PUBAID -80.31 75.45 -1.06 0.293 1.858

DENSITY -1.7647 0.7620 -2.32 0.026 2.807

KIDS 1.167 1.191 0.98 0.333 1.848

UNEMPLOY -72.91 81.21 -0.90 0.375 2.174

URBAN 60.805 9.954 6.11 0.000 1.901

Crime vs Dropout

Crime vs Urban

Crime vs unemployment

Crime vs Density Crime vs pubaid

Crime vs Kids

Crime vs Mid-west

Crime vs Neast…...

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