Skip to main content
Business LibreTexts

2.2: Official Statistics

  • Page ID
    43427
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

    ( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\id}{\mathrm{id}}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\kernel}{\mathrm{null}\,}\)

    \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\)

    \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\)

    \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    \( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

    \( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

    \( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vectorC}[1]{\textbf{#1}} \)

    \( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

    \( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

    \( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

    \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)

    Despite being aware that crime does go unreported, it is still important to estimate and attempt to measure crime in the country. However, it is essential always to be aware of the data sources strengths and weaknesses when reading crime statistics. Also, be cautious of how changing data collection techniques may alter statistics. For example, if a survey never collected data on prescription drug abuse but then all of a sudden does it could seem like prescription drugs are being abused at high rates. However, it is most likely just because it is the first time the questions got asked and there are no comparison groups.

    Official statistics are gathered from various criminal justice agencies, such as the police and courts, and represent the total number of crimes reported to the police or the number of arrests made by that agency. Remember, if an officer uses discretion and does not arrest a person, even if a crime was committed, this does not get reported.

    The Federal Bureau of Investigation’s (FBI’s) Uniform Crime Reports (UCR) is the largest, most common data on crime currently available. The UCR lists the number of crimes that were reported to the police and the number of arrests made. The link below can take you to the UCR homepage www.fbi.gov/services/cjis/ucr.

    The UCR Program’s primary objective is to generate reliable information for use in law enforcement administration, operation, and management. Various groups and agencies rely upon the UCR crime data, such as law enforcement executives, students, researchers, the media, and the public at large seeking information on crime in the nation. [1] The UCR began in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics. Every year there are four annual publications produced from data received from more than 18,000 city, university and college, county, state, tribal, and federal law enforcement agencies voluntarily participating in the program. [2]

    The UCR Program consists of four data collections: The National Incident-Based Reporting System (NIBRS), the Summary Reporting System (SRS), the Law Enforcement Officers Killed and Assaulted (LEOKA) Program, and the Hate Crime Statistics Program. The UCR also publishes special reports on Cargo Theft, Human Trafficking, and NIBRS topical studies. The UCR Program will manage the new National Use-of-Force Data Collection.

    National Incident-Based Reporting System, or NIBRS

    The National Incident-Based Reporting System, or NIBRS, was created to improve the overall quality of crime data collected by law enforcement. NIBRS is unique because it collects data on crimes reported to the police, but also incidents where multiple crimes are committed, for example when a robbery escalates into a rape. [3] NIBRS also collects information on victims, known offenders, relationships between victims and offenders, arrestees, and property involved in the crimes. See the link to go directly to NIBRS www.fbi.gov/services/cjis/ucr/nibrs

    Hate Crime Statistics

    Congress passed the Hate Crime Statistics Act, 28 U.S.C. § 534, on April 23, 1990. This required the attorney general to collect data “about crimes that manifest evidence of prejudice based on race, religion, sexual orientation, or ethnicity.” Hate crime statistics may assist law enforcement agencies, provide lawmakers with justification for certain legislation, provide the media with credible information, or simply show hate crime victims that they are not alone (FBI, 2018). See the link to go to the FBI’s hate crime statistics link www.fbi.gov/services/cjis/ucr/hate-crime.

    The FBI UCR Program’s Hate Crime Data Collection gathers data on the following biases:

    Race/Ethnicity/Ancestry

    • Anti-American Indian or Alaska Native
    • Anti-Arab
    • Anti-Asian
    • Anti-Black or African American
    • Anti-Hispanic or Latino
    • Anti-Multiple Races, Group
    • Anti-Native Hawaiian or Other Pacific Islander
    • Anti-Other Race/Ethnicity/Ancestry
    • Anti-White

    Religion

    • Anti-Buddhist
    • Anti-Catholic
    • Anti-Eastern Orthodox (Russian, Greek, Other)
    • Anti-Hindu
    • Anti-Islamic
    • Anti-Jehovah’s Witness
    • Anti-Jewish
    • Anti-Mormon
    • Anti-Multiple Religions, Group
    • Anti-Other Christian
    • Anti-Other Religion
    • Anti-Protestant
    • Anti-Atheism/Agnosticism/etc.

    Sexual Orientation

    • Anti-Bisexual
    • Anti-Gay (Male)
    • Anti-Heterosexual
    • Anti-Lesbian
    • Anti-Lesbian, Gay, Bisexual, or Transgender (Mixed Group)

    Disability

    • Anti-Mental Disability
    • Anti-Physical Disability

    Gender

    • Anti-Male
    • Anti-Female

    Gender Identity

    • Anti-Transgender
    • Anti-Gender Non-Conforming

    The types of hate crimes reported to the FBI are broken down by specific categories. The aggregate hate crime data collected for each incident include the following:

    • Incidents and offenses by bias motivation: Includes crimes committed by and crimes directed against juveniles. Incidents may include one or more offense types.
    • Victims: The types of victims collected for hate crime incidents include individuals (adults and juveniles), businesses, institutions, and society as a whole.
    • Offenders: The number of offenders (adults and juveniles), and when possible, the race and ethnicity of the offender or offenders as a group.
    • Location type: One of 46 location types can be designated.
    • Hate crime by jurisdiction: Includes data about hate crimes by state and agency.

    Law Enforcement Officers Killed and Assaulted Program LEOKA

    LEOKA provides data and training that helps keep law enforcement officers by providing relevant, high quality, potentially lifesaving information to law enforcement agencies focusing on why an incident occurred as opposed to what occurred during the incident, with the hope of preventing future incidents. [4]

    Screen-Shot-2019-02-23-at-4.41.40-PM.png
    LEOKA Data

    Exclusions from the LEOKA Program’s Data Collection

    Deaths resulting from the following are not included in the LEOKA Program’s statistics:

    • Natural causes such as heart attack, stroke, aneurysm, etc.
    • On duty, but death is attributed to their own personal situation such as domestic violence, neighbor conflict, etc.
    • Suicide

    Examples of job positions not typically included in the LEOKA Program’s statistics (unless they meet the above exception) follow:

    • Corrections/correctional officers
    • Bailiffs
    • Parole/probation officers
    • Federal judges
    • The U.S. and assistant U.S. attorneys
    • Bureau of Prison officers
    • Private security officers

    All of these official statistics are a great starting point, although, recognize they are imperfect in nature. Police agencies can change their attention to certain events, which can change the overall number of arrests. For example, if police begin cracking down on domestic violence the statistics may go up. This crackdown can make it appear that the problem has increased, although it can be related to the crackdown. Just remember, if the crime is not reported, or no arrest is made it will not get captured in the data.

    Bureau of Justice Statistics Exercise

    The BJS is relatively user-friendly. Look at crime statistics by state, region, or city, and explore different years and crime types.
    https://www.bjs.gov/index.cfm?ty=datool&surl=/arrests/index.cfm
    Examine current state AND city crime trends in the past five years.
    Second, pick a state AND city interested in living in and examine the crime trends for the past five years.


    1. U.S. Department of Justice. (2017). UCR Reports
    2. U.S. Department of Justice. (2017). UCR Reports
    3. Rantala, R. R. (2000). Effects of NIBRS on crime statistics. Bureau of Justice Statistics Special Report. U.S. Department of Justice, Office of Justice Programs. Washington, DC.
    4. FBI (2017). www.fbi.gov/services/cjis/ucr/leoka

    This page titled 2.2: Official Statistics is shared under a CC BY-SA license and was authored, remixed, and/or curated by Alison S. Burke, David Carter, Brian Fedorek, Tiffany Morey, Lore Rutz-Burri, & Shanell Sanchez (OpenOregon) .