1. Correlation between Heat Index and Violent or Nonviolent Crimes in Cities of the United States
Alison Tiangson – Western Vance High School
Tracy Neal – Fike High School

2. Introduction
In this research, heat index which includes the temperature and relative humidity, were collected to show a positive relationship between violent and nonviolent crimes between the years
Temperature was gathered from Weather Underground website
Heat Index was calculated through the National Weather Service through the National Oceanic and Atmospheric Administration (NOAA)
Crime data was collected from the FBI’s Uniform Crime Reporting program and Police Crime Statistics
Nonviolent Crimes
Burglary
Larceny (Theft)
Auto Theft
Violent Crimes
Murder
Aggravated Assault
Rape
Robbery

3. Randomly Selected Cities
Seattle, WA
Minneapolis, MN
Philadelphia, PA
Denver, CO
Fresno, CA
Atlanta, GA
Houston, TX

4. Previous Research
CBS News

5. Microsoft Excel Software
Visualizing Data
Microsoft Excel Software
Created Scatter Plots with the regression line
Calculated the regression line equation
Calculated the Pearson’s correlation coefficient (r)
Calculated the coefficient of determination (r2) value
Calculated p value – threshold value 5%

6. Results: Violent Crimes vs. Temperature

7. Results: Violent Crimes vs. Temperature

8. Violent Crimes vs. Average Temperature Pearson Correlation Coefficient (r), Determination of Coefficient (r2) and Slope Equation
City
Violent Crimes vs. Temperature r r2
Violent Crimes vs. Temperature (Avg.,Mean) Equation
p value
Houston
0.2197
y=6.0524x
Seattle
0.5575
y=2.941x
Philadelphia
0.399
y=7.0026x
Fresno
y=1.1221x
Atlanta
0.5855
y=3.5721x
Denver
0.4639
y =2.2268x
Minneapolis
0.3534
y=1.6532x

9. Results: Violent Crimes vs. Heat Index

10. Results: Violent Crimes vs. Heat Index

11. Violent Crimes vs Heat Index Pearson Correlation Coefficient (r), Determination of Coefficient (r2), and Slope Equation
City
Violent Crimes vs. Heat Index r r2
Violent Crimes vs. Heat Index Equation
p value
Houston
0.2238
y=4.9402x
Seattle
0.5672
y=2.8969x
Philadelphia
0.3588
y=6.5743x
Fresno
0.2336
y=1.1038x
Atlanta
0.5835
y=3.2603x
Denver
0.4667
y=2.2902x
Minneapolis
0.3412
y=1.626x

12. Results: Nonviolent Crimes vs. Temperature

13. Results: Nonviolent Crimes vs. Temperature

14. Nonviolent Crimes vs. Temperature r r2
Nonviolent Crimes vs. Average Temperature Pearson Correlation Coefficient (r) and Determination of Coefficient (r2)
City
Nonviolent Crimes vs. Temperature r r2
Nonviolent Crimes vs. Temperature (Avg., Mean) Equation
p value
Houston
0.0796
y=13.837x
Seattle
0.0417
y=8.7683x
Philadelphia
0.6927
y=30.132x
Fresno
.0998
y= x
Atlanta
0.2468
y=8.9267x
Denver
0.6487
y=8.2287x
Minneapolis
0.3412
y=8.5914x

15. Results: Nonviolent Crimes vs. Heat Index

16. Results: Nonviolent Crimes vs. Heat Index

17. Nonviolent Crimes vs. Heat Index Pearson Correlation Coefficient, Determination of Coefficient (r2), and Slope Equation
City
Nonviolent Crimes vs. Heat Index r r2
Nonviolent Crimes vs. Heat Index Equation
p value
Houston
0.0847
y=11.549x
Seattle
0.0418
y=8.5773x
Philadelphia
0.6577
y=29.066x
Fresno
0.095
y= x
Atlanta
0.258
y=8.3435x
Denver
0.6608
y=8.5137x
Minneapolis
0.2674
y=8.5022x

18. Conclusions
The data gathered showed similar previous results in the increase of violent and nonviolent crimes in relation to temperature and heat index with reference to the coefficient of determination, Pearson correlation coefficient and the slope equation.
Among the seven sample cities, only 4 (Seattle, Atlanta, Denver and Philadelphia) of the cities had stronger evidence proving that temperature and heat index impacted the violent or nonviolent crimes.

19. Other Variables
Collecting data of temperature and heat index on a daily basis instead of a monthly basis will better show an accurate result of their correlation to crime rate increase or decrease.
Further research needs to be done on crime versus extreme temperatures for longer periods of time in varied cities but with close population to better enhance the resources for the police departments.
There are other variables that need to be accounted for when discussing crime, such as:
population density
racial and ethnic makeup
age especially the youth
education levels
economic status
tourists

20. Acknowledgements
National Science Foundation for funding the Research Experience for Teachers Program
Appalachian State University’s Computer Science Department.
Dr. Rahman Tashakkori
Dr. Mitch Parry
Dr. Mary Beth Searcy
Fellow RET participants
Fike High School
Western Vance High School