Number, percentage and rate (per 100,000 population) of persons accused of homicide, 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.
THIS DATASET WAS LAST UPDATED AT 2:11 AM EASTERN ON SEPT. 26
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.
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.
To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:
To get these counts just for your state:
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.
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.
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 dataset provides highly detailed (Block Level) views of various demographics for Manhattan, New York city. this dataset includes information on age, race, sex, income, housing, and various other attributes. This data comes from the 2000 Us Census and was joined to the Census Tiger line files to create the output. enjoy!
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Kill Devil Hills by race. It includes the population of Kill Devil Hills across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Kill Devil Hills across relevant racial categories.
Key observations
The percent distribution of Kill Devil Hills population by race (across all racial categories recognized by the U.S. Census Bureau): 83.65% are white, 1.16% are Black or African American, 0.31% are American Indian and Alaska Native, 1.31% are Asian, 5.37% are some other race and 8.19% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Kill Devil Hills Population by Race & Ethnicity. You can refer the same here
This dataset displays the Blood Alcohol Concentration (BAC) of the driver for all fatal traffic accidents in 2006. The data is divided on a state level, and was collected from the Fatality Analysis Reporting System at: http://www-fars.nhtsa.dot.gov/States/StatesAlcohol.aspx Access Date: November 16, 2007
This dataset was created from the CDC's National Vital Statistics Reports Volume 56, Number 6. The dataset includes all data available from this report by state level and includes births by race and Hispanic origin, births to unmarried women, rates of cesarean delivery, and twin and multiple birth rates. The data are final for 2005. No value is represented by a -1. "Descriptive tabulations of data reported on the birth certificates of the 4.1 million births that occurred in 2005 are presented. Denominators for population-based rates are postcensal estimates derived from the U.S. 2000 census".
Number, rate and percentage changes in rates of homicide victims, Canada, provinces and territories, 1961 to 2024.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of Kill Devil Hills by race. It includes the distribution of the Non-Hispanic population of Kill Devil Hills across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Kill Devil Hills across relevant racial categories.
Key observations
Of the Non-Hispanic population in Kill Devil Hills, the largest racial group is White alone with a population of 6,449 (92.53% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Kill Devil Hills Population by Race & Ethnicity. You can refer the same here
Number and percentage of homicide victims, by type of firearm used to commit the homicide (total firearms; handgun; rifle or shotgun; fully automatic firearm; sawed-off rifle or shotgun; firearm-like weapons; other firearms, type unknown), Canada, 1974 to 2018.
Victims of gang-related homicides (total number of homicide victims; number of homicide victims - unknown gang-relation; number of homicide victims - known gang relation; number of gang-related homicide victims; percentage of gang-related homicide victims; rate (per 100,000 population) of gang-related homicide victims), Canada and regions, 1999 to 2024.
This dataset contains counts of deaths for California as a whole based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.
The final data tables include both deaths that occurred in California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.
The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.
HAZUS is an abbreviation for Hazards United States, and was developed by FEMA. The HAZUS dataset was designed to estimate the potential physical, economic and social losses during hazardous events such as flooding or earthquakes. To measure the social impact of these events, HAZUS includes detailed demographic data for the United States. This dataset pulls out the racial data from the demographic files, at the census block level for the Washington portion of the Portland Metropolitan Statistic Area (MSA). Attributes include Whites, Blacks, Asians, Hispanics, Hawaiian and Pacific Islanders, Native Americans, and populations stating other race. Demographics data was recent as of May 2006.
https://www.icpsr.umich.edu/web/ICPSR/studies/3399/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/3399/terms
As a contribution to nationwide efforts to more thoroughly understand urban violence, this study was conducted to assess the impact of cultural dynamics on homicide rates in Houston, Texas, and to profile homicides in the city from 1985 to 1994. This data collection provides the results of quantitative analysis of data collected from all Houston homicide cases recorded in the police murder logs for 1985-1994. Variables describe the homicide circumstances, the victim-offender relationship, the type of weapon used, and any drug- or gang-related activity involved. Other variables include the year and month in which the homicide occurred, whether the homicide occurred on a weekday or over the weekend, the motive of the homicide, whether the homicide was drug-related, whether the case was cleared by police at time of data entry, weapon type and means of killing, the relationship between the victim and the offender, whether a firearm was the homicide method, whether it was a multiple victim incident or multiple offender incident, whether the victim or the offender was younger than age 15, and the inter-racial relationship between the victim and the offender. Demographic variables include age, sex, and race of the victim as well as the offender.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Kill Devil Hills. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Kill Devil Hills population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 83.65% of the total residents in Kill Devil Hills. Notably, the median household income for White households is $87,256. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $87,256.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Kill Devil Hills median household income by race. You can refer the same here
This dataset examines the number of unidentified persons reported to the Centers for Disease Control and Preventions (CDC) National Death Index (NDI), by State, from 1980 to 2004. This report also looks at the number of unidentified human remains reported to the Federal Bureau of Investigations (FBI) National Crime Information Center (NCIC) Unidentified Person File. It describes the characteristics by race and gender and the manner of death. Highlights include the following: Between 1980 and 2004, about 10,300 unidentified human remains were reported to the National Death Index (NDI). Almost three-quarters of unidentified persons were reported by 5 states; Arizona, California, Florida, New York, and Texas. Of the 2,900 National Crime Information Center records that contained data on the manner of death, 27% were ruled homicides; 12%, accidental deaths; 7%, natural causes; and 5%, suicides. The majority of unidentified persons were white (70%); blacks made up 15% of unidentified persons; and race could not be determined in 13% of the cases. For more information about this data go to: http://www.ojp.usdoj.gov/bjs/abstract/uhrus04.htm
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Kill Devil Hills. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Kill Devil Hills median household income by race. You can refer the same here
This dataset shows where media and press are most free to express their views and opinions. Countries rankings are based on laws, violence, and deaths of reporters and journalists. This is a Different measure of freedom than the world freedom index but just as important. This dataset shows the availability of dissenting views and opinions allowed within a Country. Source URL: http://www.rsf.org/article.php3?id_article=11715
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Kill Devil Hills by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Kill Devil Hills. The dataset can be utilized to understand the population distribution of Kill Devil Hills by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Kill Devil Hills. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Kill Devil Hills.
Key observations
Largest age group (population): Male # 50-54 years (431) | Female # 55-59 years (445). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Kill Devil Hills Population by Gender. You can refer the same here
This dataset provides information about duly sworn city, university and college, county, state, tribal, and federal law enforcement officers who were feloniously killed in the line of duty from 1997-2006 in the entire United States. More non-geographic statistics about these fatalities can be found at http://www.fbi.gov/ucr/killed/2006/feloniouslykilled.html note: Data from the past 10 years do not include the officers who died as a result of the events of September 11, 2001. http://www.fbi.gov/ucr/killed/2006/table1.html
This dataset has been migrated from our Geocommons platform, and lacks a description from the original posting user. This is not a Fortiusone provided dataset. Please keep this in mind, and make of the dataset what you will. Thank you for visiting Finder!
Number, percentage and rate (per 100,000 population) of persons accused of homicide, 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.