1. Homicidal Relations Cory Mills and Tina Habib

2. Methodology Collection of Statistical Data – Racial and Ethnic Differences – Socioeconomic Living Conditions – Focus on Lee County Bivariate Correlation Analysis – Statewide Patterns How does Lee County fit in?

3. Homicide Rate per 100,000

4. Bivariate Correlation Analysis Homicide rate in 2008 (per 100,000) Population of Racial and Ethnic Groups Education Levels Unemployment Rates Household Income Levels Median Age Percentage of Urban Populations Percentage of Owner-occupied Housing Percentage below Poverty Level

5. Bivariate Correlation Analysis Homicide rate in 2008 (per 100,000) Population of Racial and Ethnic Groups Education Levels Unemployment Rates Household Income Levels Median Age Percentage of Urban Populations Percentage of Owner-occupied Housing Percentage below Poverty Level Negetive Correlation Positive Correlation Negative Correlation

6. Median Age Homicide Rate by County (per 100,000) Median Age (in yrs) Graying Population Migration of Money Infrastructure Increased cost of Living r² = 0.116

7. Education Level (LHSD) Homicide Rate by County (per 100,000) % Population with less than an HS Diploma Confusing Chart! Racial Component Socioeconomic Indicator r² = 0.079

8. Owner-Occupied Housing (OOH) Homicide Rate by County (per 100,000) % Owner-Occupied Housing Socioeconomic Indicator Stress Level Indicator r² = 0.037

9. Unemployment Homicide Rate by County (per 100,000) Unemployment Rate 2008 r² = 0.051 Socioeconomic (again) Lee County has high rates

10. State and National Comparison

11. County Comparison

12. Why is the Lee County Homicide Rate so High? High Unemployment High Education High OOH Graying Population

13. Dangers of Demographic Shift!

14. Correlations Between Variables

15. Consequences of a Gray Population Artificially Inflated Median Household Income Higher Property Cost Higher General Cost of Living Higher Unemployment Gentrification

16. Fin