Number, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2024.

Introduction

You are looking at Crime Index 2022 Mid-Year. These indices are historical and they are published periodically.

Crime Index is an estimation of overall level of crime in a given city or a country. We consider crime levels lower than 20 as very low, crime levels between 20 and 40 as being low, crime levels between 40 and 60 as being moderate, crime levels between 60 and 80 as being high and finally crime levels higher than 80 as being very high.

Safety index is, on the other way, quite opposite of crime index. If the city has a high safety index, it is considered very safe.

Is this much less accurate than governmental statistics? In some countries, governments have a detailed statistics based on a number of reported crimes per capita. Those surveys are particular good in comparing crime between two cities in that country, but are not so good in cross country comparison for the following reasons:

• People in some countries are much more likely to report a crime than in other countries
• Data could be forged by governmental institutions
• Data is not available for most of the world

Kindly give your upvotes👍 if you find this dataset worthy of experience. Good luck Thank you😁

Context

Introduction: The dataset used for this experiment is real and authentic. The dataset is acquired from UCI machine learning repository website [13]. The title of the dataset is ‘Crime and Communities’. It is prepared using real data from socio-economic data from 1990 US Census, law enforcement data from the 1990 US LEMAS survey, and crimedata from the 1995 FBI UCR [13]. This dataset contains a total number of 147 attributes and 2216 instances.

The per capita crimes variables were calculated using population values included in the 1995 FBI data (which differ from the 1990 Census values).

Content

The variables included in the dataset involve the community, such as the percent of the population considered urban, and the median family income, and involving law enforcement, such as per capita number of police officers, and percent of officers assigned to drug units. The crime attributes (N=18) that could be predicted are the 8 crimes considered 'Index Crimes' by the FBI)(Murders, Rape, Robbery, .... ), per capita (actually per 100,000 population) versions of each, and Per Capita Violent Crimes and Per Capita Nonviolent Crimes)

predictive variables : 125 non-predictive variables : 4 potential goal/response variables : 18

Acknowledgements

http://archive.ics.uci.edu/ml/datasets/Communities%20and%20Crime%20Unnormalized

U. S. Department of Commerce, Bureau of the Census, Census Of Population And Housing 1990 United States: Summary Tape File 1a & 3a (Computer Files),

U.S. Department Of Commerce, Bureau Of The Census Producer, Washington, DC and Inter-university Consortium for Political and Social Research Ann Arbor, Michigan. (1992)

U.S. Department of Justice, Bureau of Justice Statistics, Law Enforcement Management And Administrative Statistics (Computer File) U.S. Department Of Commerce, Bureau Of The Census Producer, Washington, DC and Inter-university Consortium for Political and Social Research Ann Arbor, Michigan. (1992)

U.S. Department of Justice, Federal Bureau of Investigation, Crime in the United States (Computer File) (1995)

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

Data available in the dataset may not act as a complete source of information for identifying factors that contribute to more violent and non-violent crimes as many relevant factors may still be missing.

However, I would like to try and answer the following questions answered.

1. Analyze if number of vacant and occupied houses and the period of time the houses were vacant had contributed to any significant change in violent and non-violent crime rates in communities

2. How has unemployment changed crime rate(violent and non-violent) in the communities?

3. Were people from a particular age group more vulnerable to crime?

4. Does ethnicity play a role in crime rate?

5. Has education played a role in bringing down the crime rate?

THIS DATASET WAS LAST UPDATED AT 7:11 AM EASTERN ON DEC. 1

OVERVIEW

2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

A total of 229 people died in mass killings in 2019.

The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

One-third of the offenders died at the scene of the killing or soon after, half from suicides.

About this Dataset

The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

This data will be updated periodically and can be used as an ongoing resource to help cover these events.

Using this Dataset

To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

Mass killings by year

Mass shootings by year

To get these counts just for your state:

Filter killings by state

Definition of "mass murder"

Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

Methodology

Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

This project started at USA TODAY in 2012.

Contacts

Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

This table contains data on the rate of violent crime (crimes per 1,000 population) for California, its regions, counties, cities and towns. Crime and population data are from the Federal Bureau of Investigations, Uniform Crime Reports. Rates above the city/town level include data from city, university and college, county, state, tribal, and federal law enforcement agencies. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Ten percent of all deaths in young California adults aged 15-44 years are related to assault and homicide. In 2010, California law enforcement agencies reported 1,809 murders, 8,331 rapes, and over 95,000 aggravated assaults. African Americans in California are 11 times more likely to die of assault and homicide than Whites. More information about the data table and a data dictionary can be found in the About/Attachments section.

In 2023, the violent crime rate in the United States was 363.8 cases per 100,000 of the population. Even though the violent crime rate has been decreasing since 1990, the United States tops the ranking of countries with the most prisoners. In addition, due to the FBI's transition to a new crime reporting system in which law enforcement agencies voluntarily submit crime reports, data may not accurately reflect the total number of crimes committed in recent years. Reported violent crime rate in the United States The United States Federal Bureau of Investigation tracks the rate of reported violent crimes per 100,000 U.S. inhabitants. In the timeline above, rates are shown starting in 1990. The rate of reported violent crime has fallen since a high of 758.20 reported crimes in 1991 to a low of 363.6 reported violent crimes in 2014. In 2023, there were around 1.22 million violent crimes reported to the FBI in the United States. This number can be compared to the total number of property crimes, roughly 6.41 million that year. Of violent crimes in 2023, aggravated assaults were the most common offenses in the United States, while homicide offenses were the least common. Law enforcement officers and crime clearance Though the violent crime rate was down in 2013, the number of law enforcement officers also fell. Between 2005 and 2009, the number of law enforcement officers in the United States rose from around 673,100 to 708,800. However, since 2009, the number of officers fell to a low of 626,900 officers in 2013. The number of law enforcement officers has since grown, reaching 720,652 in 2023. In 2023, the crime clearance rate in the U.S. was highest for murder and non-negligent manslaughter charges, with around 57.8 percent of murders being solved by investigators and a suspect being charged with the crime. Additionally, roughly 46.1 percent of aggravated assaults were cleared in that year. A statistics report on violent crime in the U.S. can be found here.

There has been little research on United States homicide rates from a long-term perspective, primarily because there has been no consistent data series on a particular place preceding the Uniform Crime Reports (UCR), which began its first full year in 1931. To fill this research gap, this project created a data series on homicides per capita for New York City that spans two centuries. The goal was to create a site-specific, individual-based data series that could be used to examine major social shifts related to homicide, such as mass immigration, urban growth, war, demographic changes, and changes in laws. Data were also gathered on various other sites, particularly in England, to allow for comparisons on important issues, such as the post-World War II wave of violence. The basic approach to the data collection was to obtain the best possible estimate of annual counts and the most complete information on individual homicides. The annual count data (Parts 1 and 3) were derived from multiple sources, including the Federal Bureau of Investigation's Uniform Crime Reports and Supplementary Homicide Reports, as well as other official counts from the New York City Police Department and the City Inspector in the early 19th century. The data include a combined count of murder and manslaughter because charge bargaining often blurs this legal distinction. The individual-level data (Part 2) were drawn from coroners' indictments held by the New York City Municipal Archives, and from daily newspapers. Duplication was avoided by keeping a record for each victim. The estimation technique known as "capture-recapture" was used to estimate homicides not listed in either source. Part 1 variables include counts of New York City homicides, arrests, and convictions, as well as the homicide rate, race or ethnicity and gender of victims, type of weapon used, and source of data. Part 2 includes the date of the murder, the age, sex, and race of the offender and victim, and whether the case led to an arrest, trial, conviction, execution, or pardon. Part 3 contains annual homicide counts and rates for various comparison sites including Liverpool, London, Kent, Canada, Baltimore, Los Angeles, Seattle, and San Francisco.

Number, rate and percentage changes in rates of homicide victims, Canada, provinces and territories, 1961 to 2024.

Crime rate against Children-India

Investigating Crime Trends and Patterns Across India

By Bhavna Chawla [source]

About this dataset

This dataset provides an in-depth look at crime against children throughout India. The data, collected from state and union territories throughout the country, tracks arrests made in response to a variety of crimes including infanticide, murder of children, rape of Children, kidnapping and abduction of children, foeticide, abetment of suicide, exposure and abandonment. Additionally it looks at procuration of minor girls as well as buying or selling minors for prostitution. It also illustrates arrests made related to violation or prevention under the Prohibition Of Child Marriage Act (PCMA).

The dataset paints an unfortunately dark image across India with rising numbers each year - painfully representing the suffering these innocent minors have faced over time. Through this dataset we can not only get a better understanding on who is leading the charge in terms of crime rate but also uncover startling patterns about type specified categories that are particularly egregious when it comes to number of arrests made. By examining this data more closely together we can unravel meaningful solutions which ultimately could help protect our beloved child population from needless harm and distress

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How to use the dataset

This dataset is suitable for researchers interested in learning more about crime against children as well as government planners who may want to analyze which states have higher rates of various types of crimes and identify strategies for managing them.

To use this dataset, start by examining the main columns – STATE/UT, CRIME HEAD, 2001-2012 – which provide additional information about each row such as state or UT name and type of crime committed respectively. Then you can use a visualized comparison to evaluate trends across all the listed years: a look at total numbers or changes over time will help reveal how arrests vary among different categories or within a particular year; it will also identify areas with particularly high numbers that need more attention from policy makers. These visualizations can also be compared with statistics on population density or socio-economic characteristics such as literacy rate or poverty levels to get further insights into characterizing patterns for targeted interventions that could reduce criminal activities towards vulnerable communities.

Additionally, you could use this dataset combined with other external sources/variables (governance measures taken against certain categories etc.) to build predictive models that identify relationships between risks factors associated with higher rate of specific type(s) criminal activities prevailing amongst certain age group(s). Such approaches would help contribute towards evidence informed public safety interventions, public health initiatives and legal systems strengthening over time specifically targeting those districts where higher rates are taking place so that people especially women & girls are protected from any form physical abuse & harassment leading potential threat on their living condition & livelihood opportunities eventually affecting national development levels if left unchecked regularly each year progressing forward

Research Ideas

• This dataset could be used to identify the states with the highest crime rates against children, and explore any potential correlations between crime statistics and social or economic factors in those states.
• This dataset can also be used to analyze state-wise trends over time to assess whether government initiatives aimed at curbing crimes against children have been effective or not.
• The dataset can also help researchers examine which type of crimes are most prevalent in each state/UT and come up with ways to reduce these crimes via policy measures or public outreach programs, etc

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: Crime head-wise persons arrested under crime against children during 2001-2012.csv | Column name | Description | |:---------------|:----------------------------------------------------------------| | STATE/UT | The state or union territory in India. (String) | | CRIME HEAD | The type of crime against chi...

Context

Criminologists are interested in the effect of punishment regimes on crime rates. This has been studied using aggregate data on 47 states of the USA for 1960. The data set contains the following columns:

Task:

Predict crime rate

Content

Variable - Description M - percentage of males aged 14–24 in total state population So - indicator variable for a southern state Ed - mean years of schooling of the population aged 25 years or over Po1 - per capita expenditure on police protection in 1960 Po2 - per capita expenditure on police protection in 1959 LF - labour force participation rate of civilian urban males in the age group 14-24 M.F - number of males per 100 females Pop - state population in 1960 in hundred thousand NW - percentage of nonwhites in the population U1 - unemployment rate of urban males 14–24 U2 - unemployment rate of urban males 35–39 wealth - median value of transferable assets or family income Ineq - income inequality: percentage of families earning below half the median income Prob - probability of imprisonment: ratio of number of commitments to nunumber of offenses Time - average time in months served by offenders in state prisons before their first release Crime - crime rate: number of offenses per 100,000 population in 1960

Source

Ehrlich, I. (1973) Participation in illegitimate activities: a theoretical and empirical investigation. Journal of Political Economy 81, 521–565. Vandaele, W. (1978) Participation in illegitimate activities: Ehrlich revisited. In Deterrence and Incapacitation, eds A. Blumstein, J. Cohen and D. Nagin, National Academy of Sciences, Washington DC, pp. 270–335. Venables, W., and Ripley, B. (1998). Modern Applied Statistics with S-Plus, Second Edition. Springer-Verlag.

The data given here is rounded data taken from Vandaele (1978). The column scales differ somewhat from Venables and Ripley (1998). The data was originally collected by Ehrlich from the Uniform Crime Report of the FBI and other US government sources.

Analysis

Only one of Po1 and Po2, and only one of U1 and U2, remain in the final regression, because of high collinearity. Data gives association not causal relationships. For example, does crime really increase with police expenditure? Crime is negatively associated with the probprobability of imprisonment. Crime is slightly better modeled on a log scale.

Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2024.

"Crime Statistics" is a comprehensive collection of datasets focused on various dimensions of crime within a region, state, and district provided by the National Crime Records Bureau (NCRB). This dataset collection is invaluable for researchers, policymakers, law enforcement agencies, and social welfare organizations. It provides a multifaceted view of crime, covering different victim groups and crime types, ranging from crimes against specific social groups to cybercrimes and missing person cases. The datasets included help analyze trends, formulate targeted policies, and implement crime prevention strategies.

Suburb-based crime statistics for crimes against the person and crimes against property. The Crime statistics datasets contain all offences against the person and property that were reported to police in that respective financial year. The Family and Domestic Abuse-related offences datasets are a subset of this, in that a separate file is presented for these offences that were flagged as being of a family and domestic abuse nature for that financial year. Consequently the two files for the same financial year must not be added together. Data is point in time.

Police recorded crime figures by Police Force Area and Community Safety Partnership areas (which equate in the majority of instances, to local authorities).

In 2023, the state with the highest crime rate in the United States per 100,000 inhabitants was New Mexico. That year, the crime rate was ******** crimes per 100,000 people. In comparison, New Hampshire had the lowest crime rate at ****** crimes per 100,000 people. Crime rate The crime rate in the United States has generally decreased over time. There are several factors attributed to the decrease in the crime rate across the United States. An increase in the number of police officers and an increase in income are some of the reasons for a decrease in the crime rate. Unfortunately, people of color have been disproportionately affected by crime rates, as they are more likely to be arrested for a crime versus a white person. Crime rates regionally The District of Columbia had the highest rate of reported violent crimes in the United States in 2023 per 100,000 inhabitants. The most common crime clearance type in metropolitan counties in the United States in 2020 was murder and non-negligent manslaughter. The second most dangerous city in the country in 2020 was Detroit. Detroit has faced severe levels of economic and demographic declines in the past years. Not only has the population decreased, the city has filed for bankruptcy. Despite the median household income increasing, the city still struggles financially.

Context

In this problem, we will be examining the "state" dataset, which has data from the 1970s on all fifty US states. For each state, the dataset includes the population, per capita income, illiteracy rate, murder rate, high school graduation rate, average number of frost days, area, latitude and longitude, division the state belongs to, region the state belongs to, and two-letter abbreviation.

Content

This dataset has 50 observations (one for each US state) and the following 15 variables:

Population - the population estimate of the state in 1975 Income - per capita income in 1974 Illiteracy - illiteracy rates in 1970, as a percent of the population Life.Exp - the life expectancy in years of residents of the state in 1970 Murder - the murder and non-negligent manslaughter rate per 100,000 population in 1976 HS.Grad - percent of high-school graduates in 1970 Frost - the mean number of days with minimum temperature below freezing from 1931–1960 in the capital or a large city of the state Area - the land area (in square miles) of the state state.abb - a 2-letter abreviation for each state state.area - the area of each state, in square miles x - the longitude of the center of the state y - the latitude of the center of the state state.division - the division each state belongs to (New England, Middle Atlantic, South Atlantic, East South Central, West South Central, East North Central, West North Central, Mountain, or Pacific) state.name - the full names of each state state.region - the region each state belong to (Northeast, South, North Central, or West)

Acknowledgements

MITx ANALYTIX

This project was designed to isolate the effects that individual crimes have on wage rates and housing prices, as gauged by individuals' and households' decisionmaking preferences changing over time. Additionally, this project sought to compute a dollar value that individuals would bear in their wages and housing costs to reduce the rates of specific crimes. The study used multiple decades of information obtained from counties across the United States to create a panel dataset. This approach was designed to compensate for the problem of collinearity by tracking how housing and occupation choices within particular locations changed over the decade considering all amenities or disamenities, including specific crime rates. Census data were obtained for this project from the Integrated Public Use Microdata Series (IPUMS) constructed by Ruggles and Sobek (1997). Crime data were obtained from the Federal Bureau of Investigation's Uniform Crime Reports (UCR). Other data were collected from the American Chamber of Commerce Researchers Association, County and City Data Book, National Oceanic and Atmospheric Administration, and Environmental Protection Agency. Independent variables for the Wages Data (Part 1) include years of education, school enrollment, sex, ability to speak English well, race, veteran status, employment status, and occupation and industry. Independent variables for the Housing Data (Part 2) include number of bedrooms, number of other rooms, building age, whether unit was a condominium or detached single-family house, acreage, and whether the unit had a kitchen, plumbing, public sewers, and water service. Both files include the following variables as separating factors: census geographic division, cost-of-living index, percentage unemployed, percentage vacant housing, labor force employed in manufacturing, living near a coastline, living or working in the central city, per capita local taxes, per capita intergovernmental revenue, per capita property taxes, population density, and commute time to work. Lastly, the following variables measured amenities or disamenities: average precipitation, temperature, windspeed, sunshine, humidity, teacher-pupil ratio, number of Superfund sites, total suspended particulate in air, and rates of murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, violent crimes, and property crimes.

Context

The Gun Violence Archive is an online archive of gun violence incidents collected from over 2,000 media, law enforcement, government and commercial sources daily in an effort to provide near-real time data about the results of gun violence. GVA in an independent data collection and research group with no affiliation with any advocacy organization.

Content

This dataset includes files that separate gun violence incidents by category, including deaths and injuries of children and teens, and a collection of mass shootings.

Inspiration

• What has been the trend of gun violence in the past few years?
• What states have the highest incidents per capita per year? How has this metric changed over time?
• Are officer involved shootings on the rise? Where are they most concentrated? Do they correlate with the rates of accidental deaths and mass shootings?

Acknowledgements

This dataset is owned by the Gun Violence Archive, and can be accessed in its original form here.

NCRB functions as the repository of information on crime and criminals so as to assist the investigators in linking crime to the perpetrators. Subsequently, NCRB was entrusted with the responsibility for monitoring, coordinating and implementing the Crime and Criminal Tracking Network & Systems (CCTNS). NCRB also compiles and publishes National Crime Statistics i.e. Crime in India, Accidental Deaths & Suicides and also Prison Statistics. These publications serve as principal reference point by policy makers, police, criminologists, researchers and media, both in India and abroad. NCRB has been conferred with Silver award during Digital India Awards 2016 under Open Data Championship category from the Government of India for uploading Crime Statistics since 1953 on Govt. Portal.This layer contains information on violent crime incidence (crime head-wise as well as state/ UT wise) in 2022, which was published by the Bureau on their website. Along with total violent crimes, following related information are also available in the attribute table:Murder (Section 302 IPC)Culpable Homicide not amounting to Murder (Section 304 IPC)Infanticide (Section 315 IPC)Foeticide (Section 316 IPC)Dowry Deaths (Section 304B IPC)Attempt to Commit Murder (Section 307 IPC)Attempt to Commit Culpable Homicide (Section 308 IPC)Grievous Hurt (Sections 325, 326, 326A & 326B IPC)Kidnapping and Abduction (Sections 363-369 IPC)Rape (Section 376 IPC)Attempt to Commit Rape (Section 376 r/w 511 IPC)Rioting (Sections 147-151 & 153A IPC)Robbery (Sections 392 to 394 IPC)Dacoity (Sections 395 to 398 IPC)Arson (Sections 435 to 438 IPC)Total Violent CrimesSource: https://www.ncrb.gov.in/crime-in-india.html Crime in India statistics 2022 Pg No 197 This map layer is offered by Esri India, for ArcGIS Online subscribers. If you have any question or comments, please let us know via content@esri.in.