Minnesota Clearance Percentages for Major Crimes by County (2006)

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County Murder Rape Robbery Assault Burglary Larceny Vehicle
Theft
All
Aitkin
100% nr nr 74% 21% 28% 44% 39%
Anoka
100% nr 28% 74% 10% 23% 20% 30%
Becker
nr nr 75% 71% 15% 24% 25% 35%
Beltrami
nr nr 44% 60% 15% 24% 29% 34%
Benton
nr nr 75% 87% 11% 21% 20% 41%
Big Stone
nr nr nr 40% 11% 13% 0%(a) 16%
Blue Earth
nr nr 36% 58% 12% 21% 26% 29%
Brown
nr nr 0%(a) 88% 25% 23% 55% 39%
Carlton
100% nr 0%(a) 51% 37% 29% 54% 38%
Carver
100% nr 60% 71% 14% 16% 30% 28%
Cass
nr nr 50% 61% 17% 27% 47% 37%
Chippewa
nr nr nr 88% 33% 10% 0%(a) 27%
Chisago
100% nr 100% 84% 20% 19% 25% 32%
Clay
nr nr 38% 73% 24% 17% 30% 35%
Clearwater
nr nr nr 73% 23% 22% 57% 36%
Cook
nr nr 0%(a) 59% 0%(a) 12% 45% 23%
Cottonwood
nr nr nr 90% 35% 37% 100% 53%
Crow Wing
nr nr 44% 75% 23% 29% 34% 39%
Dakota
100% nr 38% 75% 14% 27% 21% 34%
Dodge
nr nr 50% 74% 3% 13% 11% 34%
Douglas
nr nr 100% 84% 26% 45% 48% 53%
Faribault
nr nr nr 95% 20% 33% 25% 45%
Fillmore
nr nr nr 27% 9% 2% 17% 12%
Freeborn
nr nr 50% 97% 27% 19% 42% 38%
Goodhue
nr nr 0%(a) 71% 15% 26% 27% 35%
Grant
nr nr 50% 46% 9% 11% 33% 23%
Hennepin
59% 26% 18% 51% 9% 20% 9% 26%
Houston
nr nr nr 85% 43% 57% 74% 65%
Hubbard
nr nr 100% 91% 9% 37% 32% 48%
Isanti
100% nr 100% 74% 6% 16% 17% 26%
Itasca
100% nr 60% 85% 21% 34% 54% 50%
Jackson
nr nr 0%(a) 89% 0%(c) 13% 0%(a) 33%
Kanabec
nr nr 0%(a) 40% 16% 23% 21% 27%
Kandiyohi
nr nr 56% 88% 16% 25% 24% 38%
Kittson
nr nr nr 54% 80% 16% 25% 30%
Koochiching
nr nr 0%(a) 20% 10% 8% 25% 13%
Lac qui Parle
nr nr nr 50% 15% 18% 67% 23%
Lake
nr nr nr 63% 21% 27% 20% 36%
Lake Of The Woods
nr nr nr 62% 9% 10% 50% 20%
Le Sueur
nr nr nr 97% 53% 23% 70% 43%
Lyon
nr nr nr 87% 19% 28% 31% 43%
Mahnomen
nr nr 0%(a) 85% 36% 42% 50% 67%
Martin
nr nr 0%(a) 58% 17% 21% 56% 31%
McLeod
nr nr 100% 89% 19% 29% 46% 46%
Meeker
100% nr nr 71% 15% 12% 36% 32%
Mille Lacs
nr nr 33% 85% 16% 25% 18% 45%
Morrison
nr nr nr 27% 18% 26% 25% 25%
Mower
nr nr 35% 73% 24% 32% 47% 43%
Nicollet
nr nr 0%(a) 85% 14% 24% 55% 35%
Nobles
nr nr 11% 80% 22% 35% 43% 43%
Olmsted
100% nr 31% 76% 15% 26% 22% 35%
Otter Tail
100% nr 50% 89% 25% 32% 45% 48%
Pennington
nr nr nr 90% 32% 30% 50% 44%
Pine
nr nr 25% 45% 15% 11% 22% 24%
Pipestone
nr nr nr 53% 11% 10% 40% 23%
Polk
nr nr 50% 66% 16% 18% 24% 33%
Pope
nr nr nr 89% 17% 13% 20% 46%
Ramsey
78% 6% 12% 25% 6% 19% 8% 17%
Redwood
100% nr 0%(a) 74% 19% 17% 33% 33%
Renville
100% nr 100% 89% 20% 11% 31% 32%
Rice
nr nr 44% 58% 10% 17% 22% 25%
Rock
nr nr nr 96% 37% 60% 100% 68%
Roseau
nr nr nr 88% 22% 14% 57% 33%
Scott
nr nr 46% 79% 11% 21% 23% 32%
Sherburne
100% nr 60% 88% 14% 28% 23% 35%
Sibley
nr nr nr nr 0% 0%(a) nr 0%
St Louis
100% nr 29% 67% 13% 22% 24% 31%
Stearns
100% nr 48% 75% 13% 26% 22% 34%
Steele
nr nr 25% 75% 17% 31% 41% 38%
Stevens
100% nr nr 86% 32% 25% 50% 41%
Swift
nr nr nr 88% 30% 24% 64% 45%
Todd
100% nr nr 74% 33% 34% 53% 44%
Traverse
nr nr nr 64% 17% 19% 100% 32%
Wabasha
nr nr nr 82% 11% 33% 33% 42%
Wadena
100% nr nr 77% 41% 26% 58% 43%
Waseca
nr nr 67% 91% 21% 41% 67% 51%
Washington
100% nr 39% 80% 10% 20% 26% 31%
Watonwan
nr nr 0%(a) 99% 33% 25% 57% 44%
Wilkin
100% nr nr 82% 33% 24% 60% 44%
Winona
100% nr 0%(a) 78% 20% 24% 25% 38%
Wright
100% nr 33% 93% 20% 21% 22% 30%
Yellow Medicine
nr nr nr 67% 5% 7% 33% 29%

 

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Notes:

a: 1 to 10 reported crimes

b: 11 to 20 reported crimes

c: 21 to 30 reported crimes

d: 31 to 40 reported crimes

nr: no crimes reported

The data set used for this presentation (see below) is consisent with but may differ in part from other data sets provided by the Uniform Crime Reporting Program and used for other presentations in this series.

Clearance Percentage: The percentage of known or reported crimes cleared by arrest. The percentage is determined by dividing the number of arrests for a specific offense by the number of offenses reported to police. Blank cells indicate that no offenses in this category were reported to police. A zero percentage (0%) indicates that none of the reported offenses were cleared by an arrest.

Reported Crimes: The number of known crimes reported to police. The number of these crimes cleared by arrest is represented by the Clearance Percentage, calculated by dividing the number of reported crimes by the number of crimes cleared by an arrest, and is provided in a separate table.

All: Refers to all of the seven major crimes in the table: murder, rape, robbery, assault, burglary, larceny, and vehicle thef (see below)t.

Description of Source Data: “The . . . dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categoriesof crime committed in the U.S., the FBI has limited the type of crimes includedin this compilationto those crimes which people are most likely to report to police and those crimeswhich occur frequentlyenough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much informationabout these crimes is provided in this dataset. The number oftimes an offense has been reported, the number of reported offenses that havebeen cleared byarrests . . . [are] major items of information collected.” Federal Bureau of Investigation, US Departmentof Justice.

Source: Uniform Crime Reporting Program Data – Offenses Known and Clearances by Arrest

More Information on Source Data