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Statistics: Multi Regression analysis

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We want to determine the primary factors that affect Motor Vehicle Theft crime rates in the United States. The statistical analysis of the data involves multiple-regression analysis. This problem is for Graduate/Masters level

1.What are the primary determinants of Motor Vehicle Theft crimes in the United States?

2. What would you like to know about Motor Vehicle Theft crime rates that cannot be answered by this data set?

3. How does population , Income Index, Dropout, Unemployment and Density (sq.mi) affect Motor Vehicle theft crime rates? Is this expected?

4.You will want to prepare a summary of your findings to present to a management team from a national crime department. You will find and explain the regression model using a non technical discussion to explain the important factors affect on the Motor Vehicle Theft crime rate.

5. Compare the 2008 multiregression analysis ( done in this problem) to the 1987 Multi regression analysis ( OTA did the multi regression analysis for that year 1987 in problem posting ID 310040). it will be attached. Which year's motor vehicle theft crimes was more related to the variables? What can we conclude.

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Solution Summary

Multi regression analysis for statistics is examined. The primary determinants of Motor Vehicle Theft crimes in the United States are determined.

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We want to determine the primary factors that affect Motor Vehicle Theft crime rates in the United States. The statistical analysis of the data involves multiple-regression analysis. This problem is for Graduate/Masters level

Questions to answer are:

Question 1-4: please use attachment excel case 2008

1. What are the primary determinants of Motor Vehicle Theft crimes in the United States?

Step wise regression can be used to identify the relevant variables for the Motor Vehicle Theft crimes. The Simple regression approach may not yield regression model with all relevant variables in it due to high degree of correlation among the explanatory .
The regression coefficients from the final step of are given below
Coefficients Standard Error t Stat P-value
Intercept -26261 12705.19 -2.06695 0.044155
Population 0.001845 0.000336 5.486533 1.51E-06
Dropout 2252.506 873.0697 2.579985 0.012997

2. What would ...

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