Kansas Clearance Percentages for Major Crimes by County (2007)

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County
Murder
Rape
Robbery
Assault
Burglary
Larceny
Vehicle Theft
All
Allen nr 33% 33% 61% 8% 10% 17% 27%
Anderson nr 67% 0%(a) 49% 4% 8% 15% 21%
Atchison nr 33% 25% 48% 20% 17% 21% 29%
Barber nr 0%(a) nr 17% 0%(a) 0%(b) 0%(a) 3%
Bourbon nr 0%(a) 0%(a) 48% 12% 3% 6% 20%
Brown nr 0%(a) 0%(a) 62% 15% 13% 20% 35%
Butler 0%(a) 8% 20% 55% 6% 7% 14% 21%
Chase nr 100% nr 60% 0%(a) 0%(a) nr 53%
Chautauqua nr 0%(a) nr 55% 24% 13% 50% 34%
Cherokee 0%(a) 25% 0%(a) 54% 7% 6% 10% 21%
Cheyenne nr nr nr 0%(b) 0%(a) 0%(b) nr 0%
Clark nr nr nr 25% 0%(b) 0%(a) nr 6%
Clay nr 31% nr 44% 4% 5% 13% 19%
Cloud nr 17% 100% 48% 6% 4% 8% 19%
Coffey 100% 50% nr 42% 13% 13% 29% 24%
Comanche nr 0%(a) nr 33% 33% 10% nr 20%
Cowley 0%(a) 50% 0%(a) 31% 5% 10% 7% 18%
Crawford 100% 19% 18% 36% 6% 12% 10% 19%
Decatur nr nr nr 20% 20% 8% nr 13%
Dickinson 100% 8% 50% 54% 4% 7% 18% 24%
Doniphan nr 40% nr 45% 17% 6% 46% 22%
Douglas 0%(a) 17% 27% 36% 4% 10% 9% 17%
Edwards nr 0%(a) nr 100% 0%(a) 0%(a) 0%(a) 20%
Elk nr 0%(a) nr 34% 0%(c) 3% 0%(a) 14%
Ellis 0%(a) 18% 83% 64% 11% 16% 28% 28%
Ellsworth nr 0%(a) nr 16% 12% 10% 25% 13%
Finney 100% 24% 32% 73% 10% 15% 15% 38%
Ford 50% 32% 13% 60% 6% 15% 9% 30%
Franklin nr 26% 100% 59% 13% 17% 19% 33%
Geary 100% 53% 43% 58% 7% 14% 39% 37%
Gove nr 0%(a) nr 18% 0%(a) 8% 0%(a) 9%
Graham nr nr nr 64% 0%(a) 0%(b) 0%(a) 20%
Grant nr 50% nr 64% 0%(a) 14% 33% 40%
Gray nr nr nr 58% 0%(a) 0%(a) nr 29%
Greeley nr nr nr 40% 0%(a) 0%(a) nr 15%
Greenwood nr 0%(a) 100% 42% 9% 4% 14% 15%
Harper nr 0%(a) nr 58% 6% 7% 0%(a) 22%
Harvey nr 36% 25% 57% 6% 7% 5% 24%
Haskell nr nr nr 35% 11% 9% 25% 23%
Hodgeman nr nr nr 15% 5% 0%(c) 0%(a) 7%
Jackson nr 50% 50% 52% 12% 12% 27% 29%
Jefferson nr 0%(a) nr 35% 6% 4% 7% 13%
Jewell nr nr nr 50% nr 100% nr 67%
Johnson nr 16% 13% 48% 5% 15% 10% 24%
Kearny nr 25% 0%(a) 25% 5% 13% 25% 17%
Kingman nr 50% nr 58% 7% 9% 0%(a) 25%
Kiowa nr nr 0%(a) 34% 0%(a) 15% 0%(a) 21%
Labette nr 67% 14% 25% 7% 6% 6% 13%
Lane nr nr nr 47% 0%(a) 0%(a) 0%(a) 23%
Leavenworth 100% 14% 26% 39% 7% 11% 8% 22%
Lincoln nr 0%(a) nr 24% 7% 6% 0%(a) 13%
Linn nr 0%(a) nr 33% 10% 4% 18% 16%
Logan nr 0%(a) nr 63% 0%(a) 15% 0%(a) 30%
Lyon nr 12% 16% 48% 4% 9% 9% 15%
Marion nr nr nr 57% 5% 14% 0%(a) 23%
Marshall nr 0%(a) nr 0% 0%(c) 0% 0%(b) 0%
McPherson 0%(a) 38% 0%(a) 48% 11% 9% 24% 24%
Meade nr nr nr 0%(a) 0%(a) 0%(a) nr 0%(b)
Miami nr 33% 40% 37% 6% 11% 8% 19%
Mitchell nr 0%(a) nr 57% 0%(b) 7% 0%(a) 25%
Montgomery 100% 9% 21% 47% 6% 9% 11% 21%
Morris nr nr nr 22% 0%(b) 0% 0%(a) 5%
Morton nr 0%(a) nr 49% 17% 6% 0%(a) 30%
Nemaha nr 50% nr 35% 3% 0% 8% 15%
Neosho nr 0%(a) 0%(a) 26% 7% 4% 15% 13%
Norton nr 0%(a) nr 50% 7% 10% 0%(a) 25%
Osage nr 0%(a) 25% 51% 12% 2% 13% 26%
Osborne nr nr nr 13% 0%(a) 0%(b) 0%(a) 3%
Ottawa nr 67% nr 64% 0%(c) 1% 0%(a) 15%
Pawnee 0%(a) 50% 100% 54% 14% 15% 0%(a) 34%
Phillips nr 100% nr 70% 100% 100% nr 77%
Pottawatomie nr 38% 33% 34% 9% 9% 19% 19%
Pratt nr 50% nr 42% 15% 4% 20% 24%
Rawlins nr nr nr 53% 0%(a) 0%(b) 0%(a) 20%
Reno 100% 26% 18% 28% 4% 10% 8% 16%
Republic nr 100% nr 80% 14% 11% 25% 21%
Rice nr 67% nr 27% 5% 2% 0%(b) 15%
Riley 0%(a) 49% 17% 73% 13% 19% 29% 40%
Rooks nr nr nr 88% 14% 57% 100% 69%
Rush nr nr nr 42% 0%(c) 6% 0%(a) 10%
Russell 100% 0%(a) nr 48% 3% 25% 0%(a) 31%
Saline nr 50% 25% 64% 7% 12% 17% 31%
Scott nr 20% 0%(a) 44% 14% 6% nr 18%
Sedgwick 60% 52% 33% 40% 8% 12% 12% 23%
Seward 0%(a) 24% 33% 54% 5% 11% 18% 25%
Shawnee nr 7% 22% 39% 4% 2% 6% 12%
Sheridan nr nr nr 50% 0%(a) 0%(a) 100% 22%
Sherman nr 50% nr 67% 8% 9% 0%(a) 35%
Smith nr nr nr 33% 0%(a) 0%(a) 0%(a) 8%
Stafford nr nr 0%(a) 47% 5% 4% 0%(a) 13%
Stanton nr nr nr 47% 0%(a) 0%(b) nr 18%
Stevens nr nr nr 17% 6% 3% 33% 9%
Sumner nr 0%(a) 0%(a) 30% 1% 3% 3% 11%
Thomas nr 100% 0%(a) 51% 2% 13% 33% 26%
Trego nr 0%(a) nr 64% 0%(b) 12% nr 20%
Wabaunsee nr nr 100% 50% 15% 12% 25% 27%
Wallace nr nr nr 50% 0%(a) 0%(a) nr 25%
Washington nr nr nr 71% 100% 50% 0%(a) 65%
Wichita nr 0%(a) 0%(a) 63% 9% 3% 0%(a) 20%
Wilson nr 0%(a) nr 35% 3% 9% 0%(a) 17%
Woodson nr 0%(a) nr 38% 10% 2% 50% 12%
Wyandotte nr 25% 25% 45% 4% 4% 5% 17%

 

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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