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Applied Statistics

In: Business and Management

Submitted By nedaniel
Words 1030
Pages 5
GM533 Applied Managerial Statistics
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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