HiMCM: My City Crime - Worcester Polytechnic...
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HiMCM: My City Crime Introduction Crime ratings are of paramount significance to a wide range of people, from politicians and law enforcement agents worried about their affect on the to concerned parents looking to move to a safe neighborhood. Without the abundance of data collected with each arrest and the driving force of mathe- matical modeling, it is relatively simple to determine the safety of a city. To reach this conclusion, it is necessary only to interpret the data by dividing the crimes into categories based upon the type of crime, be that violent, property related, or otherwise. Then, using the dates given, an average day and week of crime can be calculated and used in conjunction with the population size of the city or metropolitan area, in this case approximately 8.8 million citizens. Most importantly, this crime rate must be compared to that of other cities of similar size to place the results into a meaningful context. Knowledge of this safety rating can lead to increased awareness both within the general population and the governing bodies, and lead to an increase in the speed in which change is effected. Objectives The group’s objective during this process was to assign a crime rating to My City that accurately depicted the the annual crime rate in reference to other major cities with similar populations. Addition- ally, there was a conscious effort made to avoid bias by assigning different weights to certain crimes, as the group members felt that this would be an ineffective method of organizing data. Instead, throughout the analysis of the data, the groups sought to divide crimes into categories based upon given data and existing legal information regarding the type of crime each offense constituted. Assumptions 1.) The data given was an accurate representation of the crime rates throughout the year 2.) Any crime involving a weapon, whether the weapon in question caused harm to another person or not, constitutes a violent crime. 3.) Any crime involving force or the threat of force is considered a violent crime. 4.) Any crime in which the victim is a child is considered a violent crime. 5.) The population of My City includes both the city itself and the metropolitan area (a total population of 8.8 million citizens) 6.) Population size is directly proportional to crime rate within the area Crime Types The following table displays the classification used by the group for each type of crime. Team #5547 HiMCM 2015 Page 1 of 13
Transcript of HiMCM: My City Crime - Worcester Polytechnic...
HiMCM: My City Crime
IntroductionCrime ratings are of paramount significance to a wide range of people, from politicians and law
enforcement agents worried about their affect on the to concerned parents looking to move to a safe neighborhood. Without the abundance of data collected with each arrest and the driving force of mathe-matical modeling, it is relatively simple to determine the safety of a city. To reach this conclusion, it is necessary only to interpret the data by dividing the crimes into categories based upon the type of crime, be that violent, property related, or otherwise. Then, using the dates given, an average day and week of crime can be calculated and used in conjunction with the population size of the city or metropolitan area, in this case approximately 8.8 million citizens. Most importantly, this crime rate must be compared to that of other cities of similar size to place the results into a meaningful context. Knowledge of this safety rating can lead to increased awareness both within the general population and the governing bodies, and lead to an increase in the speed in which change is effected.
ObjectivesThe group’s objective during this process was to assign a crime rating to My City that accurately
depicted the the annual crime rate in reference to other major cities with similar populations. Addition-ally, there was a conscious effort made to avoid bias by assigning different weights to certain crimes, as the group members felt that this would be an ineffective method of organizing data. Instead, throughout the analysis of the data, the groups sought to divide crimes into categories based upon given data and existing legal information regarding the type of crime each offense constituted.
Assumptions1.) The data given was an accurate representation of the crime rates throughout the year2.) Any crime involving a weapon, whether the weapon in question caused harm to another person or not, constitutes a violent crime.3.) Any crime involving force or the threat of force is considered a violent crime.4.) Any crime in which the victim is a child is considered a violent crime.5.) The population of My City includes both the city itself and the metropolitan area (a total population of 8.8 million citizens)6.) Population size is directly proportional to crime rate within the area
Crime TypesThe following table displays the classification used by the group for each type of crime.
!
Property!Crimes!! • Criminal!Trespass!
• Criminal!damage!
• Theft!
• Motor!vehicle!theft!
• Deceptive!practice!
• Burglary!!
• Arson!
• Other!vehicle!offenses!
• Other!offenses!involving!property!
!
Violent!Crimes!! • Assault!
• Battery!
• Criminal!sexual!assault!!
• Homicide!
• Interference!with!a!police!officer!
• Intimidation!
• Kidnapping!
• Offenses!involving!children!
• Public!peace!violations!
• Robbery!!
• Weapon!violations!
• Animal!abuse!
Narcotics/Alcohol!Related!Offenses! • Possession!
• Manufacturing,!selling,!or!delivery!of!
drugs!!
• Altering!prescriptions!
• Attempted!possession!of!narcotics!
• Delivering!controlled!substances!to!
children!under!18!
• Criminal!drug!conspiracy!
• Forfeit!property!
• Found!suspects!narcotics!
• Illegal!consumption!by!minor!
• Intoxicating!compounds!
• Liquor!license!violation!
• Possession!of!drug!equipment!
• Solicit!narcotics!on!public!way!
• Selling,!giving,!or!delivering!liquor!to!
minor!
Miscellaneous! • Gambling!
• Harassment!
• Hazardous!materials!violations!
• License!violations!
• Other!crimes!against!people!
• Parole!violations!
Sexual!Offenses!! • Obscene!telephone!calls!!
• Prostitution!
• Sexual!offenses!
• Failure!to!register!as!a!sex!offender!
Team #5547 HiMCM 2015 Page 1 of 13
!
Property!Crimes!! • Criminal!Trespass!
• Criminal!damage!
• Theft!
• Motor!vehicle!theft!
• Deceptive!practice!
• Burglary!!
• Arson!
• Other!vehicle!offenses!
• Other!offenses!involving!property!
!
Violent!Crimes!! • Assault!
• Battery!
• Criminal!sexual!assault!!
• Homicide!
• Interference!with!a!police!officer!
• Intimidation!
• Kidnapping!
• Offenses!involving!children!
• Public!peace!violations!
• Robbery!!
• Weapon!violations!
• Animal!abuse!
Narcotics/Alcohol!Related!Offenses! • Possession!
• Manufacturing,!selling,!or!delivery!of!
drugs!!
• Altering!prescriptions!
• Attempted!possession!of!narcotics!
• Delivering!controlled!substances!to!
children!under!18!
• Criminal!drug!conspiracy!
• Forfeit!property!
• Found!suspects!narcotics!
• Illegal!consumption!by!minor!
• Intoxicating!compounds!
• Liquor!license!violation!
• Possession!of!drug!equipment!
• Solicit!narcotics!on!public!way!
• Selling,!giving,!or!delivering!liquor!to!
minor!
Miscellaneous! • Gambling!
• Harassment!
• Hazardous!materials!violations!
• License!violations!
• Other!crimes!against!people!
• Parole!violations!
Sexual!Offenses!! • Obscene!telephone!calls!!
• Prostitution!
• Sexual!offenses!
• Failure!to!register!as!a!sex!offender!
Model
Team #5547 HiMCM 2015 Page 2 of 13
Model(This section details the numerical steps of the model. The section below, entitled “Discussion of the Model” explains how these steps were carried out)
Overall Crime
Week 1:Saturday--7/5/14--202 crimesSunday--7/6/14--871 crimesMonday--7/7/14--895 crimesTuesday--7/8/14--811 crimesWednesday--7/9/14--853 crimesThursday--7/10/114--815 crimesFriday--7/11/14--935 crimes
Total crimes week 1: 5382 crimes
Week 2:Saturday--7/12/14--807 crimesSunday--7/13/14--847 crimesMonday--7/14/14--801 crimesTuesday--7/15/14--811 crimesWednesday--7/16/15--837 crimesThursday--7/17/15--804 crimesFriday--7/18/15--873 crimes
Total crimes week 2: 5780 crimes
Average Days:Saturday: 807 crimes *not an average--Saturday of Week 1 starts late*Sunday: 859 crimesMonday: 848 crimesTuesday: 811 crimesWednesday: 845 crimesThursday: 809.5 crimesFriday: 904 crimes
Average number of crimes in a week: 5883.5 crimes
Crime rate per week (overall crime): Equation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizensCrime rate per week: 66.85795 crimes per 100,000 peopleCrime rate per year: 3476.6136 crimes per 100,000 people
202#
871# 895#811# 853# 815#
935#
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Team #5547 HiMCM 2015 Page 3 of 13
Week 1:Saturday--7/5/14--202 crimesSunday--7/6/14--871 crimesMonday--7/7/14--895 crimesTuesday--7/8/14--811 crimesWednesday--7/9/14--853 crimesThursday--7/10/114--815 crimesFriday--7/11/14--935 crimes
Total crimes week 1: 5382 crimes
Week 2:Saturday--7/12/14--807 crimesSunday--7/13/14--847 crimesMonday--7/14/14--801 crimesTuesday--7/15/14--811 crimesWednesday--7/16/15--837 crimesThursday--7/17/15--804 crimesFriday--7/18/15--873 crimes
Total crimes week 2: 5780 crimes
Average Days:Saturday: 807 crimes *not an average--Saturday of Week 1 starts late*Sunday: 859 crimesMonday: 848 crimesTuesday: 811 crimesWednesday: 845 crimesThursday: 809.5 crimesFriday: 904 crimes
Average number of crimes in a week: 5883.5 crimes
Crime rate per week (overall crime): Equation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizensCrime rate per week: 66.85795 crimes per 100,000 peopleCrime rate per year: 3476.6136 crimes per 100,000 people
202#
871# 895#811# 853# 815#
935#
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1000"
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Overall#Crime#Averages#
Violent Crime
Violent CrimesWeek 1Saturday--7/5/14--77 crimesSunday--7/6/14-- 360 crimesMonday--7/7/14--320 crimesTuesday--7/8/14--308 crimesWednesday--7/9/14--283 crimesThursday--7/10/14--284 crimesFriday--7/11/14-- 310 crimes
Week 2:Saturday--7/12/14-- 321 crimesSunday--7/13/14--343 crimesMonday--7/14/14--272 crimesTuesday--7/15/14--250 crimesWednesday--7/16/15-- 260 crimesThursday--7/17/15--247 crimesFriday--7/18/15--274 crimes
Average Days:Saturday: 321 crimes *not an average--Saturday of Week 1 starts late*Sunday: 351.5 crimesMonday: 296 crimesTuesday: 279 crimesWednesday: 271.5 crimesThursday: 265.5 crimesFriday: 292 crimes
Average number of crimes in a week: 2076.5 crimesEquation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizens Crime rate per week: 23.5965909 crimes per 100,000 peopleCrime rate per year: 1227.02273 crimes per 100,000 people
Team #5547 HiMCM 2015 Page 4 of 13
Violent CrimesWeek 1Saturday--7/5/14--77 crimesSunday--7/6/14-- 360 crimesMonday--7/7/14--320 crimesTuesday--7/8/14--308 crimesWednesday--7/9/14--283 crimesThursday--7/10/14--284 crimesFriday--7/11/14-- 310 crimes
Week 2:Saturday--7/12/14-- 321 crimesSunday--7/13/14--343 crimesMonday--7/14/14--272 crimesTuesday--7/15/14--250 crimesWednesday--7/16/15-- 260 crimesThursday--7/17/15--247 crimesFriday--7/18/15--274 crimes
Average Days:Saturday: 321 crimes *not an average--Saturday of Week 1 starts late*Sunday: 351.5 crimesMonday: 296 crimesTuesday: 279 crimesWednesday: 271.5 crimesThursday: 265.5 crimesFriday: 292 crimes
Average number of crimes in a week: 2076.5 crimesEquation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizens Crime rate per week: 23.5965909 crimes per 100,000 peopleCrime rate per year: 1227.02273 crimes per 100,000 people
321$351.5$
296$ 279$ 271.5$ 265.5$ 292$
0"50"100"150"200"250"300"350"400"
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f$Crim
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Violent$Crimes$
Property Crime
Week 1Saturday--7/5/14--86 crimesSunday--7/6/14-- 397 crimesMonday--7/7/14--459 crimesTuesday--7/8/14--390 crimesWednesday--7/9/14--446 crimesThursday--7/10/14--399 crimesFriday--7/11/14-- 486 crimes
Week 2:Saturday--7/12/14-- 372 crimesSunday--7/13/14--393 crimesMonday--7/14/14--414 crimesTuesday--7/15/14--419 crimesWednesday--7/16/15-- 455 crimesThursday--7/17/15--453 crimesFriday--7/18/15--468 crimes
Average Days:Saturday: 372 crimes *not an average--Saturday of Week 1 starts late*Sunday: 395 crimesMonday: 436.5 crimesTuesday: 404.5 crimesWednesday: 450.5 crimesThursday: 426 crimesFriday: 477 crimes
Average number of crimes in a week: 2961.5 crimesEquationn: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizens Crime rate per week: 33.6534091 crimes per 100,000 peopleCrime rate per year: 1749.97727 crimes per 100,000 people
Team #5547 HiMCM 2015 Page 5 of 13
Week 1Saturday--7/5/14--86 crimesSunday--7/6/14-- 397 crimesMonday--7/7/14--459 crimesTuesday--7/8/14--390 crimesWednesday--7/9/14--446 crimesThursday--7/10/14--399 crimesFriday--7/11/14-- 486 crimes
Week 2:Saturday--7/12/14-- 372 crimesSunday--7/13/14--393 crimesMonday--7/14/14--414 crimesTuesday--7/15/14--419 crimesWednesday--7/16/15-- 455 crimesThursday--7/17/15--453 crimesFriday--7/18/15--468 crimes
Average Days:Saturday: 372 crimes *not an average--Saturday of Week 1 starts late*Sunday: 395 crimesMonday: 436.5 crimesTuesday: 404.5 crimesWednesday: 450.5 crimesThursday: 426 crimesFriday: 477 crimes
Average number of crimes in a week: 2961.5 crimesEquationn: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizens Crime rate per week: 33.6534091 crimes per 100,000 peopleCrime rate per year: 1749.97727 crimes per 100,000 people
372$ 395$ 436.5$ 404.5$450.5$ 426$
477$
0"100"200"300"400"500"600"
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Sunday"
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umbe
r$of$C
rimes$
Days$of$the$Week$$
Property$Crimes$$
Narcotics/Alcohol Related Offenses
Week 1Saturday--7/5/14--26 crimesSunday--7/6/14--90 crimesMonday--7/7/14--86 crimesTuesday--7/8/14--92 crimesWednesday--7/9/14--88 crimesThursday--7/10/114--103 crimesFriday--7/11/14--101 crimes
Week 2:Saturday--7/12/14--89 crimesSunday--7/13/14--89 crimesMonday--7/14/14--84 crimesTuesday--7/15/14--104 crimesWednesday--7/16/15-- 82 crimesThursday--7/17/15--74 crimesFriday--7/18/15--93 crimes
Average Days:Saturday: 89 crimes *not an average--Saturday of Week 1 starts late*Sunday: 89.5 crimesMonday: 85 crimesTuesday: 98 crimesWednesday: 85 crimesThursday: 88.5 crimesFriday: 97 crimes
Average number of crimes in a week: 632 crimesEquation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizensCrime rate per weel: 7.1818 crimes per 100,000 peopleCrime rate per year: 373.4545 crimes per 100,000 people
Team #5547 HiMCM 2015 Page 6 of 13
Week 1Saturday--7/5/14--26 crimesSunday--7/6/14--90 crimesMonday--7/7/14--86 crimesTuesday--7/8/14--92 crimesWednesday--7/9/14--88 crimesThursday--7/10/114--103 crimesFriday--7/11/14--101 crimes
Week 2:Saturday--7/12/14--89 crimesSunday--7/13/14--89 crimesMonday--7/14/14--84 crimesTuesday--7/15/14--104 crimesWednesday--7/16/15-- 82 crimesThursday--7/17/15--74 crimesFriday--7/18/15--93 crimes
Average Days:Saturday: 89 crimes *not an average--Saturday of Week 1 starts late*Sunday: 89.5 crimesMonday: 85 crimesTuesday: 98 crimesWednesday: 85 crimesThursday: 88.5 crimesFriday: 97 crimes
Average number of crimes in a week: 632 crimesEquation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizensCrime rate per weel: 7.1818 crimes per 100,000 peopleCrime rate per year: 373.4545 crimes per 100,000 people
89# 89.5#
85#
98#
85#88.5#
97#
75#
80#
85#
90#
95#
100#
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f#Crim
es#
Days#of#the#Week#
Narco:cs/Alcohol#Related#Offenses#
Sexual Crimes
Week 1Saturday--7/5/14--8 crimesSunday--7/6/14--3 crimesMonday--7/7/14--0 crimesTuesday--7/8/14--6 crimesWednesday--7/9/14--20 crimesThursday--7/10/114--7 crimesFriday--7/11/14--16 crimes
Week 2:Saturday--7/12/14--9 crimesSunday--7/13/14--7 crimesMonday--7/14/14--2 crimesTuesday--7/15/14--14 crimesWednesday--7/16/15-- 13 crimesThursday--7/17/15--6 crimesFriday--7/18/15--14 crimes
Average Days:Saturday: 9 crimes *not an average--Saturday of Week 1 starts late*Sunday: 5 crimesMonday: 1 crimesTuesday: 10 crimesWednesday: 16.5 crimesThursday: 6.5 crimesFriday: 15 crimes
Average number of crimes in a week: 63 crimesEquation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizens Crime rate per week: 0.7159 crimes per 100,000 peopleCrime rate per year: 37.227 crimes per 100,000 people
Team #5547 HiMCM 2015 Page 7 of 13
Week 1Saturday--7/5/14--8 crimesSunday--7/6/14--3 crimesMonday--7/7/14--0 crimesTuesday--7/8/14--6 crimesWednesday--7/9/14--20 crimesThursday--7/10/114--7 crimesFriday--7/11/14--16 crimes
Week 2:Saturday--7/12/14--9 crimesSunday--7/13/14--7 crimesMonday--7/14/14--2 crimesTuesday--7/15/14--14 crimesWednesday--7/16/15-- 13 crimesThursday--7/17/15--6 crimesFriday--7/18/15--14 crimes
Average Days:Saturday: 9 crimes *not an average--Saturday of Week 1 starts late*Sunday: 5 crimesMonday: 1 crimesTuesday: 10 crimesWednesday: 16.5 crimesThursday: 6.5 crimesFriday: 15 crimes
Average number of crimes in a week: 63 crimesEquation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizens Crime rate per week: 0.7159 crimes per 100,000 peopleCrime rate per year: 37.227 crimes per 100,000 people
9"
5"
1"
10"
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15"
0"2"4"6"8"10"12"14"16"18"
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Days"of"the"Week"
Sexual"Offenses"
Miscellaneous
Week 1Saturday--7/5/14--5 crimesSunday--7/6/14--21 crimesMonday--7/7/14--30 crimesTuesday--7/8/14--15 crimesWednesday--7/9/14--16 crimesThursday--7/10/114--22 crimesFriday--7/11/14--22 crimes
Week 2:Saturday--7/12/14--16 crimesSunday--7/13/14--15 crimesMonday--7/14/14--29 crimesTuesday--7/15/14--24 crimesWednesday--7/16/15-- 27 crimesThursday--7/17/15--24 crimesFriday--7/18/15--25 crimes
Average Days:Saturday: 16 crimes *not an average--Saturday of Week 1 starts late*Sunday: 18 crimesMonday: 29.5 crimesTuesday: 19.5 crimesWednesday: 21.5 crimesThursday: 23 crimesFriday: 23.5 crimes
Average number of crimes in a week: 151 crimesEquation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizensCrime rate per week: 1.7159 crimes per 100,000 peopleCrime rate per year: 89.227 crimes per 100,000 people
Team #5547 HiMCM 2015 Page 8 of 13
Week 1Saturday--7/5/14--5 crimesSunday--7/6/14--21 crimesMonday--7/7/14--30 crimesTuesday--7/8/14--15 crimesWednesday--7/9/14--16 crimesThursday--7/10/114--22 crimesFriday--7/11/14--22 crimes
Week 2:Saturday--7/12/14--16 crimesSunday--7/13/14--15 crimesMonday--7/14/14--29 crimesTuesday--7/15/14--24 crimesWednesday--7/16/15-- 27 crimesThursday--7/17/15--24 crimesFriday--7/18/15--25 crimes
Average Days:Saturday: 16 crimes *not an average--Saturday of Week 1 starts late*Sunday: 18 crimesMonday: 29.5 crimesTuesday: 19.5 crimesWednesday: 21.5 crimesThursday: 23 crimesFriday: 23.5 crimes
Average number of crimes in a week: 151 crimesEquation: (Number of Crimes/ Population) *100,000 = Number of Crimes per 100,000 citizensCrime rate per week: 1.7159 crimes per 100,000 peopleCrime rate per year: 89.227 crimes per 100,000 people
16# 18#
29.5#
19.5# 21.5# 23# 23.5#
0"5"10"15"20"25"30"35"
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Monday"
Tuesday"
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Miscellaneous#
Crime Percentages by Category
The pie chart below displays the total number of crimes committed as the sum of the components (the varying types of crime).
Narco&cs/Alcohol,11%,
Miscellaneous,3%,
Sexual,Offenses,1%,
Violent,Crimes,35%,
Property,Crimes,50%,
Crime&Percentages&by&Category&
Comparison Between Other Cities to Establish Safety Rating
New York City Chicago Metropolitan Area My CityPopulation 8, 491, 079 9, 554, 958 8, 800, 000
Violent Crime Rate 394 900 1227Property Crime Rate 1825 3571 1750Overall Crime Rate 2219 4471 3477
The crime rates are the number or crimes per 100,000 people in a year in each area.
New York City Chicago Metropolitan Area My CityViolent Crimes 3 2 1Property Crimes 2 1 3Overall Crimes 3 1 2
Total 8 4 6
The numbers of violent crimes per 100,000 people in a year, property crimes per 100,000 people in a year, and the total number of crimes per 100,000 people in a year were found for New York City, the Chicago Metropolitan Area, and My City. Each category was ranked from 1 to 3, with 1 being the largest number of crimes and 3 being the lowest. From this system, it is clear that a higher score indi-cates a greater level of safety and is thus more desirable than a lower score. The values were then added for each area and a total value was found. For example, the table shows that New York City had the highest total ranking, thus showing that it is the safest of the three cities and the Chicago Metropoli-tan Area had the lowest total ranking, meaning it is the least safe. Therefore, My City was the middle of the three areas in terms of safety. This practice could be expanded to any given number of cities were the lowest possible score is 3, given that the cities are still only evaluated upon three specifications, and the highest score is 3n, where n is the number of areas being compared.
Team #5547 HiMCM 2015 Page 9 of 13
The numbers of violent crimes per 100,000 people in a year, property crimes per 100,000 people in a year, and the total number of crimes per 100,000 people in a year were found for New York City, the Chicago Metropolitan Area, and My City. Each category was ranked from 1 to 3, with 1 being the largest number of crimes and 3 being the lowest. From this system, it is clear that a higher score indi-cates a greater level of safety and is thus more desirable than a lower score. The values were then added for each area and a total value was found. For example, the table shows that New York City had the highest total ranking, thus showing that it is the safest of the three cities and the Chicago Metropoli-tan Area had the lowest total ranking, meaning it is the least safe. Therefore, My City was the middle of the three areas in terms of safety. This practice could be expanded to any given number of cities were the lowest possible score is 3, given that the cities are still only evaluated upon three specifications, and the highest score is 3n, where n is the number of areas being compared.
Discussion of the ModelThe aforementioned model was carried out in an effort to find the crime rate per week and per
year in My City. First, the group structured the data into separate spreadsheets by the categories referenced throughout this paper. Then, the data was organized by date within each of the sections. The group counted the number of each type of crime that occurred on a given day and recorded this information for the two weeks of data supplied in the problem. The average number of crimes that occurs on a given day of the week was then found by adding together each of the days, for example the Sunday of the first week and the Sunday of the second week, and dividing by two. This method was followed for all days of the week, with the notable eception of Saturday. A closer look at the data revealed that on 7/5/14, a Saturday and the day the collection of data began, crimes were not recorded until 7:00pm. Therefore, we chose not to include the Saturday of the first week, as a day in which crime data is collected only from the late evening onwards is not an accurate representation of the data collection during an average Saturday. Thus, the average number of crimes that occur on a Saturday is a reflection only of the number of crimes that occurred on the second Saturday, 7/12/14.These values for the average number of crimes in a day were then added together to find the average number of crimes in a week. Using the aforementioned equation, which divides the total number of crimes by the population size and subsequently multiplies the result of the quotient by 100,000 to find the crime rate per week per 100,000 citizens. This can be easily expanded to an annual crime rate by multiplying by 52, the approximate number of weeks in a year. The aforementioned comparison between cities clearly shows a relationship between a low score and a lower safety rating within the city.
Analysis of the Model (Strengths/Weaknesses)Strengths:1.) The model does not place varing weights on different crimes, thus removing any moral considera-tions from a mathematical approach2.) The model considers not only the data presented in the problem, but was expanded to predict the average number of crimes within a given time frame3.) The crime rate per 100,000 people, the standard format for crime rates used within governmental bodies, was found, thus making it incredibly simple to compare My City to others4.) The model was very simple which contributes to its flexibility in case additional data or constraints were later added. Additionally, this simplicity lends itself to an increased amount of understanding both within the general population and the government.5.) Crimes were organized according to existing legal definitions of varying types of crimes ensuring accuracy6.) The graphs included in the “Model” section of this paper clearly show which days have the highest crime activity of any given type
Weaknesses:1.) Some additional data that was originally provided was not utilized. For example, this model did not consider arrests, the domestic nature (or lack therof) of the crime, and the beat numbers2.) My City was compared to only two other cities/metropolitan areas as opposed to a larger pool of data which may have shown a flaw in the logic of the development of our safety rating
Team #5547 HiMCM 2015 Page 10 of 13
Strengths:1.) The model does not place varing weights on different crimes, thus removing any moral considera-tions from a mathematical approach2.) The model considers not only the data presented in the problem, but was expanded to predict the average number of crimes within a given time frame3.) The crime rate per 100,000 people, the standard format for crime rates used within governmental bodies, was found, thus making it incredibly simple to compare My City to others4.) The model was very simple which contributes to its flexibility in case additional data or constraints were later added. Additionally, this simplicity lends itself to an increased amount of understanding both within the general population and the government.5.) Crimes were organized according to existing legal definitions of varying types of crimes ensuring accuracy6.) The graphs included in the “Model” section of this paper clearly show which days have the highest crime activity of any given type
Weaknesses:1.) Some additional data that was originally provided was not utilized. For example, this model did not consider arrests, the domestic nature (or lack therof) of the crime, and the beat numbers2.) My City was compared to only two other cities/metropolitan areas as opposed to a larger pool of data which may have shown a flaw in the logic of the development of our safety rating
Letter to the Mayor of My CityDear Mayor,
After close analysis by a top group of mathematical modelers, we have concluded that your city is only moderately safe. Dividing the crimes into violent, property, sexual, narcotics, and miscellaneous we determined that the crime rates for each of these sections were high enough to constitute the title of moderately safe. We have devised a system through which these reference areas can be analyzed in comparison to your own city. If you review our paper, near the conclusion of the section entitled “Model” you will see your city as well as the others in question were ranked on a skill of one to three in each of three categories; violent crime, property crime, and total crime. These three specifications were then added together and a total score was giving, with a higher score indicating a safer city. The results showed that My City had a total score of six, with the lowest, and most desirable, possible score being a three and the highest, and least desirable, being a nine. To provide you with some perspective for these numbers, New York City scored a four according to this test, indicating that this city was slightly safer than My City, and the Chicago Metropolitan Area scored an eight, indicating that this area was slightly less safe than My City.
We would also like to alert you to specific crimes which may be of particular interest to you. As a team, we have provided you with the categories of crimes which are greatest within your city, as well as some examples of these particular offenses for you to peruse. The highest rate found was the section for property crimes. Violent crimes followed, with narcotic crimes close behind, ending with miscella-neous crimes and sexual crimes. Property crimes include crimes like burglary and arson. Violent crimes include crimes like murder and robbery. Narcotic crimes include crimes like illegal possession of drugs. Miscellaneous crimes include parole violations and stalking. Sexual crimes include crimes prostitution and public indecency. Our team hopes that this information will be helpful to you in the future as you look to improve My City. It is our sincere recommendation that you focus most heavily on property crimes as are the most abundant in your community.
Thank you for your time, and we hope this information was helpful to you.
Sincerely,The Q Mathematical Modeling Company
Conclusions
Team #5547 HiMCM 2015 Page 11 of 13
ConclusionsThe group’s model analyzed the data using both existing legal definitions of a myraid of crime
types as well as a crime rate based upon the standard format used by governments today. However, this does not mean that our model is necessarily provides the most accurate description of the crime within the city. It was necessary to compare our acquired information to that of other cities, and as this data may have been collected in varying ways, it is probably that it is nearly impossible to accurately determine the safety rating of a given city without some level of error or subjectiveness. Additionally there are a variety of outside factors, such as poverty levels and education backgrounds that can lead to an increase or decrease in crime rates and can not feasibly be controlled by any governing body. Thus, the group’s model is both effective and answers the proposed question while still being aware of the drawbacks, both those that could be accounted for and those that could not.
If the group had had more time, the primary priority would be to account for the beat number, the location in the city in which the crime occurred. This would have allowed the group to create a list of the police routes along which crime rates would be the lowest and inform the public. This would lead to an increased focus on the areas with high crime rates and would hopefully normalize any differences between areas over time. The group would also have liked to further analyze the data surrounding time to find the time of day during which crime is most likely to occur.
BibliographyChicago crime rates and statistics. (2015). Retrieved November 10, 2015, from
http://www.neighborhoodscout.com/il/chicago/crime/The Crime of indecent exposure. (2015). Retrieved November 10, 2015, from
http://criminal.lawyers.com/criminal-law-basics/the-crime-of-indecent-exposure.htmlCrime rates, statistics, and crime data for every city in america. (2015). Retrieved November 10, 2015, from
http://www.neighborhoodscout.com/neighborhoods/crime-rates/Differences between theft, burglary and robbery. (2015). Retrieved November 10, 2015, from
http://www.criminaldefenselawyer.com/resources/criminal-defense/criminal-offense/differences-
between-theft-burglary-robberyFBI - property crime. (n.d.). Retrieved November 10, 2015, from https://www.fbi.gov/about-us/cjis/u-cr/crime-in-
the-u.s/2012/crime-in-the-u.s.-2012/property-crime/property-crimeFBI - violent crime. (n.d.). Retrieved November 10, 2015, from https://www.fbi.gov/about-us/cjis/u-cr/crime-in-
the-u.s/2011/crime-in-the-u.s.-2011/violent-crime/violent-crimeHow to calculate crime rate. (2015). Retrieved November 10, 2015, from
http://www.bairanalytics.com/community/blog/how-to-calculate-crime-rate-2/New York crime rates and statistics. (2015). Retrieved November 10, 2015, from
http://www.neighborhoodscout.com/ny/crime/Property crime. (n.d.). Retrieved November 10, 2015, from http://www.udel.edu/soc/tammya/pdfs/Prop-erty
Crime.pdfProperty crimes. (2015). Retrieved November 10, 2015, from http://criminal.findlaw.com/criminal-
charges/property-crimes.htmlStalking charges. (n.d.). Retrieved November 10, 2015, from http://criminal-law.freeadvice.com/criminal-
law/violent_crimes/stalking-charges.htmUnited states crime rates 1960 - 2014. (2014). Retrieved November 10, 2015, from
http://www.disastercenter.com/crime/uscrime.htm
Team #5547 HiMCM 2015 Page 12 of 13
Chicago crime rates and statistics. (2015). Retrieved November 10, 2015, from http://www.neighborhoodscout.com/il/chicago/crime/
The Crime of indecent exposure. (2015). Retrieved November 10, 2015, from http://criminal.lawyers.com/criminal-law-basics/the-crime-of-indecent-exposure.html
Crime rates, statistics, and crime data for every city in america. (2015). Retrieved November 10, 2015, from
http://www.neighborhoodscout.com/neighborhoods/crime-rates/Differences between theft, burglary and robbery. (2015). Retrieved November 10, 2015, from
http://www.criminaldefenselawyer.com/resources/criminal-defense/criminal-offense/differences-
between-theft-burglary-robberyFBI - property crime. (n.d.). Retrieved November 10, 2015, from https://www.fbi.gov/about-us/cjis/u-cr/crime-in-
the-u.s/2012/crime-in-the-u.s.-2012/property-crime/property-crimeFBI - violent crime. (n.d.). Retrieved November 10, 2015, from https://www.fbi.gov/about-us/cjis/u-cr/crime-in-
the-u.s/2011/crime-in-the-u.s.-2011/violent-crime/violent-crimeHow to calculate crime rate. (2015). Retrieved November 10, 2015, from
http://www.bairanalytics.com/community/blog/how-to-calculate-crime-rate-2/New York crime rates and statistics. (2015). Retrieved November 10, 2015, from
http://www.neighborhoodscout.com/ny/crime/Property crime. (n.d.). Retrieved November 10, 2015, from http://www.udel.edu/soc/tammya/pdfs/Prop-erty
Crime.pdfProperty crimes. (2015). Retrieved November 10, 2015, from http://criminal.findlaw.com/criminal-
charges/property-crimes.htmlStalking charges. (n.d.). Retrieved November 10, 2015, from http://criminal-law.freeadvice.com/criminal-
law/violent_crimes/stalking-charges.htmUnited states crime rates 1960 - 2014. (2014). Retrieved November 10, 2015, from
http://www.disastercenter.com/crime/uscrime.htm
Team #5547 HiMCM 2015 Page 13 of 13
