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Minnesota – Called “the land of 10,000 lakes”, this mid-western state was sold to the early USA by France as part of the Louisiana Purchase. For many years, it was known as a great center of prairie agriculture but by the mid-20th century, it had also developed a thriving industrial presence. Today that industrial base has been augmented by new and high-tech industries and scientific research centers.

Around 5.4 million people call the state home, of which a little over 60% inhabit the greater Minneapolis-Saint Paul “twin cities” metropolitan area. It ranks 30th in the US for population density. Economically, Minnesota is an affluent state, being one of the wealthiest in the Union. Its standard of living index is the highest in the USA and it also features towards the top in education assessment.

1.86 Average violent crime per 1,000
23.62 Average property crime per 1,000

Minnesota household incomes are in excess of 10% higher than US averages at $68,000. Specifically, in the Minneapolis-Saint Paul area, the excess is even higher at 25% above US norms, being $77,000. State per capita income at nearly $36,000 (2017) is approximately 10% higher than US averages.

The crimes statistics for the state are roughly at half the national average. Specifically:

  • It’s the 14th safest state for property crime (where 1st = lowest crime)
  • Minnesota’s violent crime levels have a ratio of 0.53 to the national average with 1.86 crimes per 1,000 against the national average of 3.47. This makes it the 5th safest state for violent crime.
  • Property crime levels are similarly low at 23.62 per 1,000 compared to the national average of 40.43 – giving a ratio of 0.58.

The safest areas statistically are:

  1. Big Lake
  2. Orono
  3. Hibbing
  4. Lino Lakes
  5. Grand Rapids

Safest Cities in Minnesota, 2019

RankCityViolent CrimesProperty CrimesViolent Crime RateProperty Crime Rate
1Big Lake1590.0935.499
2Orono111220.5526.124
3Hibbing281121.7446.978
4Lino Lakes91950.4269.221
5Grand Rapids191371.68612.156
6South Lake Minnetonka111140.8919.236
7Hopkins332531.81413.910
8New Ulm231741.72713.067
9Rosemount142080.5778.576
10Farmington132090.5679.120
11Northfield281971.3659.604
12St. Peter151491.27312.650
13Hutchinson222801.58920.222
14Centennial Lakes101500.91313.691
15Eden Prairie328240.49712.789
16Lakeville445980.6999.498
17Chaska222550.8349.665
18Champlin262791.06511.426
19New Hope294061.38319.364
20Elk River244290.97617.444
21Plymouth639640.80412.303
22Savage264570.82614.512
23Golden Valley184520.83520.979
24North Mankato161621.17111.856
25Rochester2242,1431.94418.598
26Marshall322592.34318.960
27Owatonna324631.24017.939
28Moorhead908892.09320.675
29Minnetonka358990.66317.023
30Crystal504652.15820.066
31Fairmont112561.09725.531
32Sartell202851.15316.424
33Shakopee697571.67618.384
34Robbinsdale373682.54425.301
35Faribault695412.91022.814
36Anoka415052.35128.958
37Mendota Heights152321.32620.506
38Edina231,0610.44320.434
39Willmar684903.47825.060
40Ramsey144180.52515.689
41Cottage Grove157490.41420.660
42Eagan581,2700.86819.011
43Stillwater213951.08320.367
44Winona496181.81022.829
45Maple Grove501,2420.70517.501
46Alexandria414002.98129.078
47Woodbury591,2930.84318.477
48Sauk Rapids112860.79920.771
49Buffalo133340.80220.610
50North St. Paul192771.51522.081
51St. Paul1,99610,9356.50835.654
52Hastings364941.58821.790
53Rogers143441.07526.419
54Inver Grove Heights746772.09919.203
55Columbia Heights515042.58125.507
56Brooklyn Park2812,1673.49726.971
57Bloomington1402,5901.63430.220
58Mounds View113910.83729.743
59North Branch202241.93321.645
60Austin526392.10625.879
61New Brighton285931.23026.041
62South St. Paul755193.70625.649
63St. Louis Park491,3210.99326.765
64Richfield939222.57725.549
65Brooklyn Center1251,0764.03434.722
66Apple Valley651,1661.24022.235
67White Bear Lake447031.68826.971
68Mankato1071,3012.54530.942
69Burnsville1011,7531.64428.531
70Brainerd705545.26041.632
71Cloquet215101.73442.121
72Prior Lake306481.13724.570
73St. Cloud2562,7893.77041.068
74Oakdale609112.12932.327
75Fridley831,0313.01637.469
76Minneapolis4,61419,44611.01346.414
77Coon Rapids1011,7711.61628.338
78Duluth2793,8193.23344.250
79Blaine561,9410.87730.396
80Forest Lake307361.51537.164
81West St. Paul899714.50049.095
82Maplewood921,9112.26146.966
83Roseville891,9482.45953.818
84Bemidji561,2683.72084.230

METHODOLOGY

To identify the safest cities in Minnesota, we reviewed the most recent FBI Uniform Crime Report statistics. A total of 7,639 cities were factored into this ranking with populations ranging from 7,639 to 4,007,147. However, we eliminated any cities that failed to submit a complete crime report to the FBI and removed cities with populations under 10,000.

Overall, data from 8,793 law enforcement agencies that represented more 193 million of the US population helped us draw interesting insights between the size of the police force and incidence of crime.

There are two broad classifications of crimes: violent crimes and non-violent crimes. According to the FBI, “Violent crime is composed of four offenses: murder and non-negligent manslaughter, rape, robbery, and aggravated assault. Violent crimes are defined in the UCR Program as those offenses that involve force or threat of force. Property crime includes the offenses of burglary, larceny-theft, motor vehicle theft, and arson. The object of the theft-type offenses is the taking of money or property, but there is no force or threat of force against the victims. ”

We computed the total number of crimes reported by each city by adding violent crimes and property crimes. We then rated them using the population of the city and created a crime rate as the number of crimes per 1,000 population. Then we transformed the total crime rate variable so that the skewness was reduced and we normalized it so the final number became a score between 0 and 1.

Next, we computed a new variable called Police Adequacy (TotalCrimes / Number of police employees). We consider that the smaller the police adequacy statistic is, the safer the city is. We transformed and normalized this police adequacy variable also, resulting in a score between 0 and 1. Finally, we combined the two scores to create a safety score for each city.

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