This collection consists of modified records from CENSUS OF POPULATION AND HOUSING, 1960 PUBLIC USE SAMPLE [UNITED STATES]: ONE-IN-ONE HUNDRED SAMPE (ICPSR 7756). The original records consisted of 120-character household records and 120-character person records, whereas the new modified records are rectangular (each person record is combined with the corresponding household record) with a length of 188, after the deletion of some items. Additional information was added to the data records including typical educational requirement for current occupation, occupational prestige score, and group identification code. This version differs from the original public-use sample in the following ways: ages of persons 15-74 are included, 10 percent of the Black population from each file is included, and Mexican Americans (identified by a Spanish surname) from outside Arizona, California, Colorado, New Mexico, and Texas are not included. This dataset uses the 1970 equivalent occupational codes. The Census Bureau originally used two separate codes for the 1970 and 1960 files, but these have been modified and are now identical.

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

Abstract (en): This data collection contains extracts of the original DUALabs Special Fifth Count ED/BG Summary Tapes. They are comprised of limited demographic and socioeconomic variables for 27 states in the continental United States. Data are provided at the county, minor civil division, enumeration district, and block group levels for total population and Spanish heritage population for the following states: Minnesota, Nevada, Wyoming, Indiana, Kansas, Nebraska, Oklahoma, South Dakota, Colorado, Arizona, Utah, North Dakota, Montana, Idaho, Missouri, Washington, Iowa, Louisiana, Arkansas, Ohio, Michigan, Wisconsin, Illinois, Oregon, Texas, New Mexico, and California. Demographic variables provide information on race, age, sex, country and place of origin, income, and family status and size. The data were obtained by ICPSR from the National Chicano Research Network, Survey Research Center, Institute for Social Research, University of Michigan. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.. A total of 27 states in the continental United States. 2011-08-18 SAS, SPSS, and Stata setups have been added to this data collection.2006-01-12 All files were removed from dataset 28 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 28 and flagged as study-level files, so that they will accompany all downloads.

DEC. 22, 2022 – After a historically low rate of change between 2020 and 2021, the U.S. resident population increased by 0.4%, or 1,256,003, to 333,287,557 in 2022, according to the U.S. Census Bureau’s Vintage 2022 national and state population estimates and components of change released today.

Net international migration — the number of people moving in and out of the country — added 1,010,923 people between 2021 and 2022 and was the primary driver of growth. This represents 168.8% growth over 2021 totals of 376,029 – an indication that migration patterns are returning to pre-pandemic levels. Positive natural change (births minus deaths) increased the population by 245,080.

“There was a sizeable uptick in population growth last year compared to the prior year’s historically low increase,” said Kristie Wilder, a demographer in the Population Division at the Census Bureau. “A rebound in net international migration, coupled with the largest year-over-year increase in total births since 2007, is behind this increase.”

Regional Patterns The South, the most populous region with a resident population of 128,716,192, was the fastest-growing and the largest-gaining region last year, increasing by 1.1%, or 1,370,163. Positive net domestic migration (867,935) and net international migration (414,740) were the components with the largest contributions to this growth, adding a combined 1,282,675 residents.

The West was the only other region to experience growth in 2022, having gained 153,601 residents — an annual increase of 0.2% for a total resident population of 78,743,364 — despite losing 233,150 residents via net domestic migration (the difference between residents moving in and out of an area). Natural increase (154,405) largely accounted for the growth in the West.

The Northeast, with a population of 57,040,406, and the Midwest, with a population of 68,787,595, lost 218,851 (-0.4%) and 48,910 (-0.1%) residents, respectively. The declines in these regions were due to negative net domestic migration.

Changes in State Population Increasing by 470,708 people since July 2021, Texas was the largest-gaining state in the nation, reaching a total population of 30,029,572. By crossing the 30-million-population threshold this past year, Texas joins California as the only states with a resident population above 30 million. Growth in Texas last year was fueled by gains from all three components: net domestic migration (230,961), net international migration (118,614), and natural increase (118,159).

Florida was the fastest-growing state in 2022, with an annual population increase of 1.9%, resulting in a total resident population of 22,244,823.

“While Florida has often been among the largest-gaining states,” Wilder noted, “this was the first time since 1957 that Florida has been the state with the largest percent increase in population.”

It was also the second largest-gaining state behind Texas, with an increase of 416,754 residents. Net migration was the largest contributing component of change to Florida’s growth, adding 444,484 residents. New York had the largest annual numeric and percent population decline, decreasing by 180,341 (-0.9%). Net domestic migration (-299,557) was the largest contributing component to the state’s population decline.

Eighteen states experienced a population decline in 2022, compared to 15 and DC the prior year. California, with a population of 39,029,342, and Illinois, with a population of 12,582,032, also had six-figure decreases in resident population. Both states’ declining populations were largely due to net domestic outmigration, totaling 343,230 and 141,656, respectively.

Puerto Rico Population Changes In 2022, Puerto Rico’s population was 3,221,789. This reflects a decrease of 1.3%, or 40,904 people, between 2021 and 2022.

Puerto Rico’s population decline resulted from negative net international migration (-26,447) and negative natural change (-14,457), where deaths outnumber births.

                            **###Components of Change for States**

In 2022, 24 states experienced negative natural change, or natural decrease. Florida had the highest natural decrease at -40,216, followed by Pennsylvania (-23,021) and Ohio (-19,543). In 2021, 25 states had natural decrease.

Of the 26 states and the District of Columbia where births outnumbered deaths, Texas (118,159), California (106,155) and New York (35,611) had the highest natural increase.

All 50 states and the District of Columbia saw positive net international migration with California (125,715), Florida (125,629) and Texas (118,614) having the largest gains.

The biggest gains from net domestic migration last year were in Florida (318,855), Texas (230,961) and North Carolina (99,796), while the biggest losses were in California (-343,230), New York (-299,557) and Illinois...

The Hispanic EPESE provides data on risk factors for mortality and morbidity in Mexican Americans in order to contrast how these factors operate differently in non-Hispanic White Americans, African Americans, and other major ethnic groups. The Wave 7 dataset comprises the sixth follow-up of the baseline Hispanic EPESE (HISPANIC ESTABLISHED POPULATIONS FOR THE EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1993-1994: [ARIZONA, CALIFORNIA, COLORADO, NEW MEXICO, AND TEXAS] [ICPSR 2851]). The baseline Hispanic EPESE collected data on a representative sample of community-dwelling Mexican Americans, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. The public-use data cover demographic characteristics (age, sex, type of Hispanic race, income, education, marital status, number of children, employment, and religion), height, weight, social and physical functioning, chronic conditions, related health problems, health habits, self-reported use of dental, hospital, and nursing home services, and depression. Subsequent follow-ups provide a cross-sectional examination of the predictors of mortality, changes in health outcomes, and institutionalization, and other changes in living arrangements, as well as changes in life situations and quality of life issues. During this 7th Wave (dataset 1), 2010-2011, re-interviews were conducted either in person or by proxy, with 659 of the original respondents. This Wave also includes 419 re-interviews from the additional sample of Mexican Americans aged 75 years and over with higher average-levels of education than those of the surviving cohort who were added in Wave 5, increasing the total number of respondents to 1,078. The Wave 7 Informant Interviews dataset (dataset 2) includes data which corresponds to the sixth follow-up of the baseline Hispanic EPESE Wave 7 and included re-interviews with 1,078 Mexican Americans aged 80 years and older. During these interviews, participants were asked to provide the name and contact information of the person they are "closer to" or they "depend on the most for help." These INFORMANTS were contacted and interviewed regarding the health, function, social situation, finances, and general well-being of the ongoing Hispanic EPESE respondents. Information was also collected on the informant's health, function, and caregiver responsibilities and burden. This dataset includes information from 925 informants, more than two-thirds of whom were children of the respective respondents.

Congressional districts of the 99th Congress are matched to census geographic areas in this file. The areas used are those from the 1980 census. Each record contains geographic data, a congressional district code, and the total 1980 population count. Ten states were redistricted for the 99th Congress: California, Hawaii, Louisiana, Maine, Mississippi, Montana, New Jersey, New York, Texas, and Washington. The data for the other 40 states and the District of Columbia are identical to that for the 98th Congress. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08404.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

This data was obtained from https://mappingpoliceviolence.us/.

Mapping Police Violence is a 501(c)(3) organization that publishes the most comprehensive and up-to-date data on police violence in America to support transformative change.

This is a database set on openly sharing information on police violence in America.

Some information on this data according to their website: Our data has been meticulously sourced from official police use of force data collection programs in states like California, Texas and Virginia, combined with nationwide data from The Gun Violence Archive and the Fatal Encounters database, two impartial crowdsourced databases. We've also done extensive original research to further improve the quality and completeness of the data; searching social media, obituaries, criminal records databases, police reports and other sources to identify the race of 90 percent of all victims in the database.

We believe the data represented on this site is the most comprehensive accounting of people killed by police since 2013. Note that the Mapping Police Violence database is more comprehensive than the Washington Post police shootings database: while WaPo only tracks cases where people are fatally shot by on-duty police officers, our database includes additional incidents such as cases where police kill someone through use of a chokehold, baton, taser or other means as well as cases such as killings by off-duty police. A recent report from the Bureau of Justice Statistics estimated approximately 1,200 people were killed by police between June, 2015 and May, 2016. Our database identified 1,100 people killed by police over this time period. While there are undoubtedly police killings that are not included in our database (namely, those that go unreported by the media), these estimates suggest that our database captures 92% of the total number of police killings that have occurred since 2013. We hope these data will be used to provide greater transparency and accountability for police departments as part of the ongoing work to end police violence in America.

This data set represents the average population density, in number of people per square kilometer multiplied by 10 for the year 2000, compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data set is the 2000 Population Density by Block Group for the Conterminous United States (Hitt, 2003).

The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) RF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011).

Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).

Context

The death penalty was authorized by 32 states, the Federal Government, and the U.S. Military. While Connecticut, Maryland, and New Mexico no longer have death penalty statutes, they do currently incarcerate death-sentenced offenders. Texas leads the nation in the number of executions since the death penalty was reinstated in 1976. California, Florida, Texas, and Pennsylvania have the largest death row populations.

The following crimes are Capital Murder in Texas:

• murder of a peace officer or fireman who is acting in the lawful discharge of an official duty and who the person knows is a peace officer or fireman;

• murder during the commission or attempted commission of kidnapping, burglary, robbery, aggravated sexual assault, arson, obstruction or retaliation, or terroristic threat;

• murder for remuneration or promise of remuneration or employs another to commit murder for remuneration or promise of remuneration;

• murder during escape or attempted escape from a penal institution;

• murder, while incarcerated in a penal institution, of a correctional employee or with the intent to establish, maintain, or participate in a combination or in the profits of a combination;

• murder while incarcerated in a penal institution for a conviction of murder or capital murder;

• murder while incarcerated in a penal institution serving a life sentence or a 99 year sentence for a conviction of aggravated kidnapping, aggravated sexual assault, or aggravated robbery;

• murder of more than one person during the same criminal transaction or during different criminal transactions but the murders are committed pursuant to the same scheme or course of conduct;

• murder of an individual under ten years of age; or

• murder in retaliation for or on account of the service or status of the other person as a judge or justice of the supreme court, the court of criminal appeals, a court of appeals, a district court, a criminal district court, a constitutional county court, a statutory county court, a justice court, or a municipal court.

Content

The Texas Department of Criminal Justice publishes various details, including the last words, of every inmate on death row they execute. This dataset includes information on the name, age, race, county, date, and last words of Texas death row inmates from 1982 to 2017.

Acknowledgments

This dataset on last statements by executed offenders was obtained here: https://www.tdcj.state.tx.us/death_row/dr_executed_offenders.html

Start a new kernel

This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across states. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rates are based on deaths occurring in the specified week/month and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly/monthly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly/monthly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

Intraspecific competition influences population and community dynamics and occurs via two mechanisms. Exploitative competition is an indirect effect that occurs through use of a shared resource and depends on resource availability. Interference competition occurs by obstructing access to a resource and may not depend on resource availability. Our study tested whether the strength of interference competition changes with protozoa population density. We grew experimental microcosms of protozoa and bacteria under different combinations of protozoan density and basal resource availability. We then solved a dynamic predator–prey model for parameters of the functional response using population growth rates measured in our experiment. As population density increased, competition shifted from exploitation to interference, and competition was less dependent on resource levels. Surprisingly, the effect of resources was weakest when competition was the most intense. We found that at low population densities, competition was largely exploitative and resource availability had a large effect on population growth rates, but the effect of resources was much weaker at high densities. This shift in competitive mechanism could have implications for interspecific competition, trophic interactions, community diversity, and natural selection. We also tested whether this shift in the mechanism of competition with protozoa density affected the structure of the bacterial prey community. We found that both resources and protozoa density affected the structure of the bacterial prey community, suggesting that competitive mechanism may also affect trophic interactions.

In 2023, Texas had the highest number of forcible rape cases in the United States, with 15,097 reported rapes. Delaware had the lowest number of reported forcible rape cases at 194. Number vs. rate It is perhaps unsurprising that Texas and California reported the highest number of rapes, as these states have the highest population of states in the U.S. When looking at the rape rate, or the number of rapes per 100,000 of the population, a very different picture is painted: Alaska was the state with the highest rape rate in the country in 2023, with California ranking as 30th in the nation. The prevalence of rape Rape and sexual assault are notorious for being underreported crimes, which means that the prevalence of sex crimes is likely much higher than what is reported. Additionally, more than a third of women worry about being sexually assaulted, and most sexual assaults are perpetrated by someone the victim knew.

This dataset comprises the third follow-up of the baseline Hispanic EPESE, HISPANIC ESTABLISHED POPULATIONS FOR THE EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1993-1994: ARIZONA, CALIFORNIA, COLORADO, NEW MEXICO, AND TEXAS, and provides information on 1,682 of the original respondents. The Hispanic EPESE collected data on a representative sample of community-dwelling Mexican-American elderly, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. The primary purpose of the series was to provide estimates of the prevalence of key physical health conditions, mental health conditions, and functional impairments in older Mexican Americans and to compare these estimates with those for other populations. The Hispanic EPESE attempted to determine whether certain risk factors for mortality and morbidity operate differently in Mexican Americans than in non-Hispanic White Americans, African Americans, and other major ethnic groups. The public-use data cover background characteristics (age, sex, type of Hispanic race, income, education, marital status, number of children, employment, and religion), height, weight, social and physical functioning, chronic conditions, related health problems, health habits, self-reported use of dental, hospital, and nursing home services, and depression. The follow-ups provide a cross-sectional examination of the predictors of mortality, changes in health outcomes, and institutionalization and other changes in living arrangements, as well as changes in life situations and quality of life issues. The vital status of respondents from baseline to this round of the survey may be determined using the Vital Status file (Part 2). This file contains interview dates from the baseline as well as vital status at Wave IV (respondent survived, date of death if deceased, proxy-assisted, proxy-reported cause of death, proxy-true). The first follow-up of the baseline data (Hispanic EPESE Wave II, 1995-1996 [ICPSR 3385]) followed 2,438 of the original 3,050 respondents, and the second follow-up (Hispanic EPESE Wave III, 1998-1999 [ICPSR 4102]) followed 1,980 of these respondents. Hispanic EPESE, 1993-1994 (ICPSR 2851), was modeled after the design of ESTABLISHED POPULATIONS FOR EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1981-1993: EAST BOSTON, MASSACHUSETTS, IOWA AND WASHINGTON COUNTIES, IOWA, NEW HAVEN, CONNECTICUT, AND NORTH CENTRAL NORTH CAROLINA and ESTABLISHED POPULATIONS FOR EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1996-1997: PIEDMONT HEALTH SURVEY OF THE ELDERLY, FOURTH IN-PERSON SURVEY DURHAM, WARREN, VANCE, GRANVILLE, AND FRANKLIN COUNTIES, NORTH CAROLINA.

Abstract (en): The School District Data Book (SDDB) is an education database and information system. It contains an extensive set of data on children, their households, and the nation's school systems. Under the sponsorship of the National Center for Education Statistics, the Bureau of the Census has produced special tabulation files using the basic record files of the 1990 Census of Population and Housing by school district. These tabulation files contain aggregated data describing attributes of children and households in school districts. Data are organized by seven types of tabulation records: (1) characteristics of all households, (2) characteristics of all persons, (3) characteristics of households with children, (4) characteristics of parents living with children, (5) children's household characteristics, (6) children's parents' characteristics, and (7) children's own characteristics. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. All public elementary and secondary education agencies in operation during 1990-1991 in the 50 states and the District of Columbia. 2006-10-27 Variable names were corrected in SAS and SPSS setup files. The processing note in the codebook was also updated to reflect the corrections.2006-01-12 All files were removed from dataset 139 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 138 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 137 and flagged as study-level files, so that they will accompany all downloads.2002-05-29 Seventeen additional datasets (Parts 140-156) were added to the collection, including data for two states previously not covered -- Vermont and Washington -- and additional data for Arkansas, California, Illinois, Massachusetts, Michigan, Minnesota, New Jersey, Pennsylvania, and Texas. (1) Some states have multiple data files because they have large numbers of cases. (2) Two data files are not included in this release. They are: Washington, Part 3, and Wisconsin, Part 4.