Questions 1-5: Data for 51 U.S. "states" (50 states, plus the District of Columbia) was used to examine the relationship between violent crime rate (violent crimes per 100,000 persons per year) and the predictor variables of urbanization (percentage of the population living in urban areas) and poverty rate. The output for the regression analysis is as follows: 1. 2. 3. Predictor Constant Urban Poverty Analysis of Variance Source Regression 5 Residual Error 45 Total 50 A. B. Coef -321.90 4.689 39.34 C. D. A. B. C. D. DF Α. B. C. None of them All of them SE Coef 148.20 1.654 13.52 Based on the p-value listed above in the F-test, how many of the predictors are useful for predicting the violent crime rate? SS 2060459 882169 2942628 = Exactly one of them At least one of them T Р -2.17 0.035 2.83 0.007 2.91 0.006 MS 412091 - 19604 F P 0.000 Which of the following represents the fitted relationship between crime, urbanization, and poverty? Crime = -321.9+4.689(urban) +39.34(poverty) + e Crime = -321.9+ 1.654(urban) + 13.52(poverty) + e Crime 148.20 +4.689(urban) +39.34(poverty) + e Crime = 148.20+ 1.654(urban) + 13.52(poverty) + e Which predictor variable has the strongest relationship to the explanation of crime? Beta 1.23 0.84 0.92 Urban Poverty Urban and Poverty are equal since both are significant 8. 9. 7. C 2 F 6. t
Questions 1-5: Data for 51 U.S. "states" (50 states, plus the District of Columbia) was used to examine the relationship between violent crime rate (violent crimes per 100,000 persons per year) and the predictor variables of urbanization (percentage of the population living in urban areas) and poverty rate. The output for the regression analysis is as follows: 1. 2. 3. Predictor Constant Urban Poverty Analysis of Variance Source Regression 5 Residual Error 45 Total 50 A. B. Coef -321.90 4.689 39.34 C. D. A. B. C. D. DF Α. B. C. None of them All of them SE Coef 148.20 1.654 13.52 Based on the p-value listed above in the F-test, how many of the predictors are useful for predicting the violent crime rate? SS 2060459 882169 2942628 = Exactly one of them At least one of them T Р -2.17 0.035 2.83 0.007 2.91 0.006 MS 412091 - 19604 F P 0.000 Which of the following represents the fitted relationship between crime, urbanization, and poverty? Crime = -321.9+4.689(urban) +39.34(poverty) + e Crime = -321.9+ 1.654(urban) + 13.52(poverty) + e Crime 148.20 +4.689(urban) +39.34(poverty) + e Crime = 148.20+ 1.654(urban) + 13.52(poverty) + e Which predictor variable has the strongest relationship to the explanation of crime? Beta 1.23 0.84 0.92 Urban Poverty Urban and Poverty are equal since both are significant 8. 9. 7. C 2 F 6. t
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:### Questions 1-5: Relationship Between Violent Crime Rate and Predictor Variables in U.S. States
Data from 51 U.S. "states" (50 states, plus the District of Columbia) was used to examine the relationship between the violent crime rate (violent crimes per 100,000 persons per year) and predictor variables of urbanization (percentage of the population living in urban areas) and poverty rate. The output for the regression analysis is as follows:
#### Regression Output:
```
Predictor Coef SE Coef t P Beta
Constant -321.90 148.20 -2.17 0.035 1.23
Urban 4.69 1.64 2.83 0.007 0.84
Poverty 39.34 13.52 2.91 0.006 0.92
Analysis of Variance (ANOVA)
Source DF SS MS F P
Regression 2 2060465 412093 21.06 0.000
Residual Error 48 8812629 19640
Total 50 124240629
```
#### Questions:
1. **Based on the p-value listed above in the F-test, how many of the predictors are useful for predicting the violent crime rate?**
- A. None of them
- B. All of them
- C. Exactly one of them
- D. At least one of them
2. **Which of the following represents the fitted relationship between crime, urbanization, and poverty?**
- A. Crime = -321.9 + 4.689(urban) + 39.34(poverty) + e
- B. Crime = -321.9 + 1.654(urban) + 13.52(poverty) + e
- C. Crime = 148.20 + 4.689(urban) + 39.34(poverty) + e
- D. Crime = 148.20 + 1.654(urban) + 13.52(poverty) + e
3. **Which predictor variable has the strongest relationship to the explanation of crime?**
- A. Urban
-
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