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VICTIM DEMOGRAPHIC INFORMATION
SOUTH DAKOTA STATISTICAL ANALYSIS CENTER
INTRODUCTION
The purpose of South Dakota's project was to provide a detailed description of crime victims in the state based on an analysis of incident-based reports. Victim information is an important tool for use by law enforcement in preventing crime. It can also be used by the public for community policing and other efforts to prevent crime in their communities.
This is South Dakota's first attempt to use the incident-based crime data from NIBRS. We did not collect data specifically for this project, but used 1999 data as submitted by police departments, sheriffs' offices, and the Department of Criminal Investigation (DCI). Victim data were obtained from the NIBRS database. Information from the incident reports include victim and offender relationships; whether they are within the family or outside of the family; whether the offender is known or not known by the victim; indication of domestic abuse; rate of alcohol/drug involvement; common locations; and use and involvement of weapons. We contracted with a programmer to write queries against the victim segment of the NIBRS software and to design reports based on those queries. Data from the queries were combined with demographic information and other data elements to produce the reports. We have not yet been able to provide these types of reports to local law enforcement agencies or other outside entities, so we do not have any feedback on them. We continue to collect more incident-based data and improve on data quality.
Our goal is to provide extensive and detailed information on the victims of crime in the state of South Dakota. We hope to be able to produce reports such as these and make them available to treatment programs, counseling programs, prosecuting attorneys, and to policymakers and legislators who set enforcement policies for law enforcement agencies and create statutes for the punishment of offenders and the treatment of victims.
BACKGROUND
In 1991, the South Dakota Statistical Analysis Center (SAC) received a grant from the Bureau of Justice Statistics (BJS) for the South Dakota Uniform Crime Reporting Redesign Project. The purpose of the project was to develop and implement the reporting standards established by the Federal Bureau of Investigation (FBI) for the National Incident-Based Reporting System (NIBRS). The South Dakota NIBRS Advisory Committee, an advisory committee of local law enforcement representatives, was formed. Based on its recommendation, the state computer agency, Information Services (IS), was hired to write the NIBRS software.
A software system for mandatory data elements as well as the mandatory supplemental reporting was developed. This software was a DOS-based data entry package with search features and basic report features. South Dakota began its conversion from UCR (Uniform Crime Reporting) to NIBRS in the latter part of 1993. On January 1, 1994, the SAC began accepting NIBRS data from participating agencies. The South Dakota SAC is somewhat unusual in that it serves as the FBI clearinghouse for the submission of UCR/NIBRS data.
In July of 1995, the South Dakota SAC began testing the NIBRS software in conjunction with the FBI. Testing continues and progress is being made toward becoming a "NIBRS-certified" state. As the industry standard became a Windows-based environment, the software offered by the state needed to be changed. In 1998, a private vendor was hired to develop a Windows-based NIBRS software program. The newly designed software, which uses Access 2.0 as the basic format, is very user friendly, unlike the DOS-based software. Under the new system, the data must be error free prior to submission to the SAC, since the design of the screens will not allow the user to progress until the information is entered correctly. This process greatly decreases the amount of time the SAC spends correcting erroneous data. In March of 1999, participating agencies began the beta testing of the new software, and the software was distributed during the summer. Software is provided free of charge and training will be offered either on-site or regionally. Testing of the system continues as South Dakota moves toward NIBRS certification by the FBI.
Participation in the local NIBRS program in South Dakota is voluntary. Reporting agencies may choose to submit crime statistics via UCR or NIBRS. When South Dakota becomes certified, however, all reporting agencies shall submit data via NIBRS. South Dakota's reporting agencies represent approximately 82% of the population. In both 1997 and 1998, the FBI reported South Dakota's population to be 738,000.
OBTAINING DATA
In 1999, the South Dakota SAC received NIBRS data from 32 local police departments (29%), 28 sheriff's offices (43%), and the South Dakota Division of Criminal Investigation (DCI), which provides statewide coverage for the reporting of NIBRS incidents by reporting only when the local jurisdiction does not participate. The SAC office receives data from the local agencies via hard copy, diskette, or modem. The data are accepted from agencies that use the old DOS-based NIBRS software, CLEM software (outside vendor that meets South Dakota NIBRS criteria), or the new Windows-based software. (The old DOS-based NIBRS system data and CLEM data are imported into the new NIBRS software.) Reports are run against the data using Access 2.0 and report generators designed by our private vendor. These reports are sent to the agencies to verify their accuracy.
ANALYSIS TOPIC
To demonstrate the potential uses of the NIBRS data, the SAC chose a sample topic, demographic information on victims, for analysis using this new software system. South Dakota does not report any information regarding victims except for the crime of murder. Increasingly, the SAC receives requests for information about the victims of crimes, especially domestic violence. Information on victims is an important resource for law enforcement when trying to prevent crime. Victim information is also important to the public as more and more communities use community policing and other means to prevent crime from happening to them, their families, and their neighbors. More data about crimes and, in particular, victims, arm law enforcement and the public with the power of knowledge to aid in crime prevention. In addition, funding sources available for victims of crime programs are increasing. It is important to have accurate, detailed statistics as resource material and for the underlying documentation.
Victim information may be obtained from the NIBRS database. For crimes against person or robbery, incident reports include victim and offender relationships; whether they are within the family or outside of the family; whether the offender is known or not known by the victim; indication of domestic abuse; rate of alcohol/drug involvement; common locations; and use and involvement of weapons.
Information on the relationship between offenders and their victims is useful to treatment programs that deal with violent offenders, outreach or counseling programs that serve abused children and battered spouses, prosecuting attorneys who are involved with victim-witness programs, and policymakers and legislators who set enforcement policies for law enforcement agencies and create statutes for the punishment of offenders and treatment of victims.
ANALYSIS PROCEDURE
We contracted with a programmer to write queries against the victim segment of the new NIBRS software and to design reports based on those queries. The following reports were developed:
- Primary Location of Offense
- Victim Age by Crime Type
- Victim Gender by Crime Type
- Victim Race by Crime Type
- Victim Type by Crime Type
- Victim Residence by Crime Type
- Victim Injury Type by Crime Type
- Victim/Offender Relationship Type by Crime Type
- Victim Ethnicity by Crime Type
- Victim Gang Affiliation by Crime Type
- Victim Count by Crime Type
- Homicide Details
- Law Enforcement Victims
- Type of Activity by Assignment Type
- Type of Activity by Cleared Type
- Type of Activity by Weapon Type
- Personal Injury by Weapon Type
- Time of Assaults
- Victim Domestic Violence by Crime Type
The data from the queries can be combined with the demographic information (age, gender, race, etc.) and the other data elements (victim type, resident status, type of injury, etc.) to enable SAC staff to perform detailed analyses on these data collected by the victim segment of the State of South Dakota Incident Report.
Additionally, the victim data are linked to an offense code. By counting these offenses, we will be able to analyze the number of offenses not reported in the UCR program such as bribery; counterfeiting/forgery; vandalism/destruction/damage of property; drug/narcotic offenses; embezzlement; extortion/blackmail; fraud offenses; gambling; and kidnapping/abduction offenses.
REPORT DEVELOPMENT
As stated before, the South Dakota SAC is somewhat unusual in that the UCR and NIBRS databases are managed by SAC staff. Therefore, UCR and NIBRS information is readily available by merely turning on the desktop computer. We did not collect data specifically for this project; rather, we used 1999 data as submitted by police departments, sheriffs' offices, and the DCI.
The data and codes reside in two different databases. The administrative, offense, victim, property, and offender/arrestee data are contained in five separate tables. Relationships exist between the administrative segment and the four other segment tables for the ORI number and the incident number fields. If a particular ORI /incident number record is deleted from the administrative segment, it is deleted from the other four segment tables. The administrative segment must contain the particular ORI and incident numbers or the record cannot be added to any of the four segment tables.
Agencies access NIBRS with a user ID and password. Data are entered by agencies using forms. The forms do not allow entry unless the edit command is selected. This makes it difficult to inadvertently change data. The forms contain field and form edits. After an incident has been added to NIBRS or changes have been made, it must be error checked again or the incident will not be accepted by the state's database. Exports to the state are done via hard copy, diskette, or modem.
Our modus operandi regarding crime data is that we do not release an individual department's data without its permission. Once the annual report Crime in South Dakota is published (generally the fall of the year), aggregate numbers are available upon request.
NIBRS is programmed in Microsoft Access 2.0. To create queries, a grid called Query By Example is used. Using SQL, the queries link tables together, summarize data, include criteria parameters, and perform whatever function the user requests. The criteria parameters contained in the queries use values entered by the user on a form. Reports are generated based on the queries. The reports identify the criteria used to generate the report. Screen captures of the program used can be viewed in the section View Screen Captures of the NIBRS Analysis Software.
We are continuing to work the "bugs" out of the software until the FBI certifies South Dakota as a NIBRS state. Some of the issues/problems we have and continue to encounter include use of the occurrence date vs. reporting date, incidents with multiple offenses, and data quality checks.
VICTIM DATA REPORTS
Included below are some of the reports generated by the SAC system. Included are: 1) Victim Age by Crime Type; 2) Victim Gender by Crime Type; 3) Victim Race by Crime Type; 4) Victim Residence by Crime Type; 5) Victim Injury Type by Crime Type; 6) Victim/Offender Relationship by Crime Type; and 7) Victim Domestic Violence and Referral by Crime Type.
Victim data are collected to describe the victims involved in the incident. A separate set of victim data is submitted for each of the victims (up to 999) involved in the incident. There must be at least one set of victim data for each crime incident.
For offenses with "Individual" victims, there were 3,783 victims reported in the first six months of 1999.
Victim Age by Crime Type
Age of Victim is to be reported either as an exact age, a range of years, or as unknown. An age is required for each "Individual" type victim. If the exact age is unknown, an approximate "age" can be reported. Any range in years is acceptable.
| Example: If a deceased female victim appeared to be a teenager, the report could be "13 to 19." |
Below is the table produced by the SAC NIBRS software. One
percent (44) of victims were under the age of ten. Ten percent (387) were juveniles,
53% (2,005) were adults, and 37% (1,391) were unknown. However, 62% (27 out of 60)
of the victims of sex offenses (Forcible Rape, Forcible Sodomy, Sexual Assault with an
Object, and Forcible Fondling) were juveniles.
| Unk Juv | Under 10 | 10 - 12 | 13 - 14 | 15 | 16 | 17 | 18 | 19 | Unk Adult | 20 | 21 | 22 | 23 | 23 | 25 - 29 | 30 - 34 | 35 - 39 | 40 - 44 | 45 - 49 | 50 - 54 | 55 - 59 | 60 - 64 | 65 and over | Total | |
| 09A Murder/NNM | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 1 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 1 |
| 09B Negligent Manslaughter | -- | -- | -- | 1 | -- | -- | -- | -- | -- | -- | -- | 1 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 2 |
| 11A Forcible Rape | -- | 4 | 1 | 8 | 2 | 1 | 2 | 1 | 2 | 3 | 3 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 33 |
| 11B Forcible Sodomy | -- | -- | -- | 1 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 1 | -- | -- | -- | -- | 2 |
| 11C Sex Assault w/ Object | -- | -- | -- | 1 | -- | -- | -- | -- | -- | -- | -- | 2 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 3 |
| 11D Forcible Fondling | -- | 5 | 6 | 2 | 3 | 1 | -- | -- | -- | 2 | 1 | -- | -- | -- | -- | 1 | -- | -- | -- | 1 | -- | -- | -- | -- | 22 |
| 120 Robbery | -- | -- | 1 | -- | -- | -- | -- | -- | -- | 1 | -- | -- | 1 | -- | -- | -- | -- | -- | 1 | -- | -- | -- | -- | -- | 4 |
| 13A Aggravated Assault | 1 | -- | 1 | 5 | 5 | 3 | 1 | 2 | 3 | 4 | 4 | 3 | 6 | 4 | 4 | 11 | 15 | 15 | 10 | 4 | 2 | 1 | -- | 1 | 105 |
| 13B Simple Assault | -- | 19 | 17 | 31 | 14 | 25 | 23 | 23 | 28 | 36 | 19 | 19 | 21 | 17 | 19 | 68 | 53 | 56 | 47 | 14 | 12 | 6 | 1 | 3 | 571 |
| 13C Intimidation | -- | -- | -- | -- | -- | -- | 1 | -- | 1 | 1 | -- | -- | -- | -- | -- | -- | 2 | 3 | -- | 2 | -- | 1 | 1 | 1 | 13 |
| 200 Arson | 1 | -- | -- | -- | -- | -- | -- | -- | -- | 5 | -- | -- | -- | -- | -- | 2 | 2 | -- | -- | 1 | -- | -- | 1 | 1 | 13 |
| 220 Burglary/B&E | 7 | 3 | -- | 2 | -- | 1 | 4 | 13 | 10 | 190 | 9 | 11 | 8 | 5 | 6 | 20 | 20 | 23 | 32 | 22 | 19 | 8 | 5 | 29 | 447 |
| 23A Pocket Picking | -- | -- | -- | 1 | 1 | -- | 1 | 1 | -- | 1 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 1 | -- | -- | -- | 6 |
| 23B Purse Snatching | -- | 1 | -- | -- | -- | -- | -- | -- | 1 | -- | -- | -- | -- | -- | -- | 2 | -- | -- | -- | -- | -- | -- | -- | 1 | 5 |
| 23C Shoplifting | 63 | -- | -- | -- | -- | -- | -- | -- | -- | 82 | -- | -- | -- | -- | -- | 1 | -- | -- | -- | -- | -- | -- | -- | -- | 146 |
| 23D Theft From Building | 8 | -- | 3 | 7 | 9 | 8 | 5 | 7 | 1 | 104 | 6 | 6 | 8 | 7 | 3 | 13 | 11 | 10 | 9 | 11 | 7 | 12 | 2 | 20 | 277 |
| 23E Theft from Coin Machine | -- | -- | -- | -- | -- | -- | -- | -- | -- | 16 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 16 |
| 23F Theft from Vehicle | 4 | -- | -- | -- | 5 | 8 | 9 | 12 | 9 | 56 | 9 | 5 | 7 | 8 | 3 | 13 | 21 | 18 | 12 | 18 | 12 | 3 | 4 | 3 | 239 |
| 23G Theft of Vehicle Parts | 1 | -- | -- | 1 | -- | -- | 2 | 4 | 2 | 25 | -- | -- | 3 | 2 | -- | 3 | 2 | 4 | 5 | 5 | 1 | 3 | 3 | 2 | 68 |
| 23H Other Larceny | 7 | 5 | 11 | 21 | 8 | 9 | 10 | 5 | 10 | 231 | 5 | 8 | 12 | 1 | 5 | 26 | 31 | 41 | 36 | 25 | 21 | 8 | 14 | 39 | 589 |
| 240 Motor Vehicle Theft | 1 | -- | -- | -- | -- | -- | 1 | 4 | 4 | 33 | 2 | 1 | 5 | 2 | 1 | 9 | 2 | 6 | 4 | 3 | 3 | 1 | 1 | 8 | 91 |
| 250 Counterfeit/ Forgery | -- | -- | -- | -- | 1 | 1 | -- | -- | 1 | 75 | 1 | 5 | -- | 1 | 2 | 4 | 2 | 2 | 5 | 4 | 4 | 2 | -- | 3 | 113 |
| 26A Theft by False Pretense | -- | 1 | -- | -- | -- | -- | -- | -- | -- | 24 | -- | 1 | -- | -- | -- | 3 | 1 | 1 | 1 | 2 | -- | 1 | -- | 5 | 40 |
| 26B Credit Card | -- | -- | -- | -- | -- | -- | -- | -- | -- | 3 | -- | -- | 1 | -- | -- | 1 | 3 | -- | 1 | -- | -- | -- | -- | -- | 9 |
| 26C Impersonation | -- | -- | -- | -- | -- | -- | -- | -- | -- | 4 | -- | -- | -- | -- | 1 | -- | -- | -- | -- | -- | -- | -- | -- | -- | 5 |
| 270 Embezzlement | -- | -- | -- | -- | -- | -- | -- | -- | -- | 16 | -- | -- | -- | -- | -- | -- | 1 | -- | 1 | 1 | -- | 1 | -- | -- | 20 |
| 280 Stolen Property | 1 | -- | 1 | 1 | -- | -- | -- | -- | -- | 9 | 1 | -- | -- | -- | -- | -- | 3 | -- | 1 | -- | 1 | -- | -- | 1 | 19 |
| 290 Destruction / Vandalism | 11 | 4 | 6 | 3 | 3 | 13 | 18 | 16 | 10 | 365 | 26 | 17 | 17 | 25 | 7 | 47 | 36 | 58 | 51 | 55 | 31 | 24 | 16 | 50 | 909 |
| 36A Incest | -- | 2 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 2 |
| 36B Statutory Rape | -- | -- | -- | 7 | 4 | 2 | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | 13 |
| Total | 105 | 44 | 47 | 92 | 55 | 72 | 77 | 88 | 82 | 1286 | 86 | 79 | 90 | 72 | 51 | 226 | 206 | 238 | 217 | 170 | 114 | 71 | 48 | 167 | 3783 |
Victim Gender by Crime Type
Sex of Victim is to be indicated in this data element as Male, Female, or Unknown.
Below is the table produced by the software. From January - June, 1999, 31% (1,167) of the victims were females, 43% (1,623) of the victims were male and 26% (993) were unknown. Males are more likely to be victims of crime, except for sex offenses.
| Female | Male | Unknown | Total | |
| 09A Murder/NNM | -- | 1 | -- | 1 |
| 09B Negligent Manslaughter | -- | 2 | -- | 2 |
| 11A Forcible Rape | 33 | -- | -- | 33 |
| 11B Forcible Sodomy | 1 | 1 | -- | 2 |
| 11C Sex Assault w/ Object | 2 | 1 | -- | 3 |
| 11D Forcible Fondling | 16 | 6 | -- | 22 |
| 120 Robbery | -- | 3 | 1 | 4 |
| 13A Aggravated Assault | 35 | 66 | 4 | 105 |
| 13B Simple Assault | 295 | 270 | 6 | 571 |
| 13C Intimidation | 6 | 7 | -- | 13 |
| 200 Arson | 4 | 4 | 5 | 13 |
| 220 Burglary/B&E | 126 | 194 | 127 | 447 |
| 23A Pocket Picking | 3 | 3 | -- | 6 |
| 23B Purse Snatching | 4 | 1 | -- | 5 |
| 23C Shoplifting | -- | 2 | 144 | 146 |
| 23D Theft From Building | 83 | 114 | 80 | 277 |
| 23E Theft from Coin Machine | 1 | 1 | 14 | 16 |
| 23F Theft from Vehicle | 76 | 145 | 18 | 239 |
| 23G Theft of Vehicle Parts | 16 | 34 | 18 | 68 |
| 23H Other Larceny | 161 | 249 | 179 | 589 |
| 240 Motor Vehicle Theft | 23 | 48 | 20 | 91 |
| 250 Counterfeit/Forgery | 22 | 20 | 71 | 113 |
| 26A Theft by False Pretense | 10 | 8 | 22 | 40 |
| 26B Credit Card | 4 | 2 | 3 | 9 |
| 26C Impersonation | 1 | -- | 4 | 5 |
| 270 Embezzlement | -- | 5 | 15 | 20 |
| 280 Stolen Property | 8 | 6 | 5 | 19 |
| 290 Destruction / Vandalism | 223 | 429 | 257 | 909 |
| 36A Incest | 2 | -- | -- | 2 |
| 36B Statutory Rape | 12 | 1 | -- | 13 |
| Total | 1167 | 1623 | 993 | 3783 |
Victim Race By Crime Type
Race of Victim is to be reported as one of the following: White, Black, American Indian/Alaskan Native, Asian/Pacific Islander, or Unknown.
Below is the table produced. Of the 3,783 victims, 65% (2,468) were White, 5% (186) were American Indian/Alaska Native, .4% (17) were Black, and .2% (7) were Asian/Pacific Islander. Twenty-nine percent (1105) were Unknown. However, 67% (2 out of 3) of the victims of offenses resulting in death (Murder/Non-negligent Manslaughter and Negligent Manslaughter) were American Indians/Alaska Natives.
| White | Black | American Indian/Alaska Native | Asian/Pacific Islander | Unknown | Total | |
| 09A Murder/NNM | -- | -- | 1 | -- | -- | 1 |
| 09B Negligent Manslaughter | 1 | -- | 1 | -- | -- | 2 |
| 11A Forcible Rape | 22 | -- | 7 | -- | 4 | 33 |
| 11B Forcible Sodomy | 2 | -- | -- | -- | -- | 2 |
| 11C Sex Assault w/ Object | 3 | -- | -- | -- | -- | 3 |
| 11D Forcible Fondling | 19 | -- | 3 | -- | -- | 22 |
| 120 Robbery | 2 | -- | 1 | -- | 1 | 4 |
| 13A Aggravated Assault | 79 | 2 | 17 | -- | 7 | 105 |
| 13B Simple Assault | 472 | 9 | 68 | 1 | 21 | 571 |
| 13C Intimidation | 11 | -- | 1 | -- | 1 | 13 |
| 200 Arson | 7 | -- | 1 | -- | 5 | 13 |
| 220 Burglary/B&E | 286 | -- | 22 | -- | 139 | 447 |
| 23A Pocket Picking | 6 | -- | -- | -- | -- | 6 |
| 23B Purse Snatching | 4 | -- | 1 | -- | -- | 5 |
| 23C Shoplifting | 2 | -- | -- | -- | 144 | 146 |
| 23D Theft From Building | 174 | 1 | 3 | -- | 99 | 277 |
| 23E Theft from Coin Machine | 2 | -- | -- | -- | 14 | 16 |
| 23F Theft from Vehicle | 209 | 1 | 3 | -- | 26 | 239 |
| 23G Theft of Vehicle Parts | 50 | -- | -- | -- | 18 | 68 |
| 23H Other Larceny | 369 | 2 | 18 | 2 | 198 | 589 |
| 240 Motor Vehicle Theft | 58 | -- | 8 | 1 | 24 | 91 |
| 250 Counterfeit/Forgery | 36 | 1 | 2 | -- | 74 | 113 |
| 26A Theft by False Pretense | 16 | -- | 1 | -- | 23 | 40 |
| 26B Credit Card | 6 | -- | -- | -- | 3 | 9 |
| 26C Impersonation | 1 | -- | -- | -- | 4 | 5 |
| 270 Embezzlement | 4 | -- | -- | -- | 16 | 20 |
| 280 Stolen Property | 10 | -- | 2 | -- | 7 | 19 |
| 290 Destruction / Vandalism | 604 | 1 | 26 | 3 | 275 | 909 |
| 36A Incest | 2 | -- | -- | -- | -- | 2 |
| 36B Statutory Rape | 11 | -- | -- | -- | 2 | 13 |
| Total | 2468 | 17 | 186 | 7 | 1105 | 3783 |
Victim Residence by Crime Type
Residence of Victim is to be reported as one of the following: Resident, Non-Resident, or Unknown.
Below is the table produced. The majority of victims (67%) were Residents; Non-Residents comprised 8% of victims, while 26% were unknown. Residents were victimized more often for every crime category.
| Resident | Non-Resident | Unknown | Total | |
| 09A Murder/NNM | 1 | -- | -- | 1 |
| 09B Negligent Manslaughter | 2 | -- | -- | 2 |
| 11A Forcible Rape | 27 | 2 | 4 | 33 |
| 11B Forcible Sodomy | 2 | -- | -- | 2 |
| 11C Sex Assault w/ Object | 3 | -- | -- | 3 |
| 11D Forcible Fondling | 21 | 1 | -- | 22 |
| 120 Robbery | 2 | 1 | 1 | 4 |
| 13A Aggravated Assault | 79 | 19 | 7 | 105 |
| 13B Simple Assault | 489 | 59 | 23 | 571 |
| 13C Intimidation | 11 | 2 | -- | 13 |
| 200 Arson | 9 | -- | 4 | 13 |
| 220 Burglary/B&E | 305 | 21 | 121 | 447 |
| 23A Pocket Picking | 4 | 2 | -- | 6 |
| 23B Purse Snatching | 5 | -- | -- | 5 |
| 23C Shoplifting | 34 | -- | 112 | 146 |
| 23D Theft From Building | 172 | 22 | 83 | 277 |
| 23E Theft from Coin Machine | 5 | -- | 11 |