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Context
This list ranks the 3 cities in the Young County, TX by Non-Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.
https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
This dataset contains information about the demographics of all US cities and census-designated places with a population greater or equal to 65,000. This data comes from the US Census Bureau's 2015 American Community Survey. This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 3 cities in the Young County, TX by Multi-Racial Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 3 cities in the Young County, TX by Multi-Racial Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
City, Population Size, African American, Asian/Pacific Islander, Latino, White, Foreign-born, Speaks a language other than English at home, Single parent households, Households with children, Average household size, 0-5 years, 6-11 years, 12-17 years, 18-24 years, 25-34 years, 35-44 years, 45-54 years, 55-64 years,Ages 65 and older, Ages 17 and younger. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
Per RCW 47.04.010, "population center" includes incorporated cities and towns, including their urban growth areas, and census-designated places in Washington State. The WSDOT Population Center dataset combines the WSDOT Incorporated City Limits dataset (May 2021) with the Office of Financial Management’s Census Designated Places (2020 Census) Dataset. Identification of Population Centers enables WSDOT to address the Complete Streets requirement under RCW 47.04.035 and to otherwise identify locations prioritized in the 2021 WSDOT Active Transportation Plan (ATP). WSDOT may also recognize other developed areas as exhibiting land use patterns consistent with the definition of population center, that are not currently captured by this data layer.This data layer assists WSDOT in prioritizing active transportation improvements in areas where people congregate and access destinations, and where travel distances between destinations align with typical distances travelled by users of pedestrian and bicycle modes. These areas are a priority because they serve the broadest range of users and potential users of the transportation system, including the very young, very old, and people with disabilities. In this dataset, each Population Center includes information for the “Place Name”, the “Place Type” (city/town, Urban Growth Area outside of city limits, or Census Designated Place), and whether or not the Population Center intersects a State Route (“yes” indicates that there is an intersection with a State Route, “no” indicates that there is no intersection.). The dataset will be updated as needed. Please direct questions about the Population Centers dataset to: Grace.Young@wsdot.wa.gov.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The data is from:
https://simplemaps.com/data/world-cities
We're proud to offer a simple, accurate and up-to-date database of the world's cities and towns. We've built it from the ground up using authoritative sources such as the NGIA, US Geological Survey, US Census Bureau, and NASA.
Our database is:
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 3 cities in the Young County, TX by Hispanic American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 3 cities in the Young County, TX by Native Hawaiian and Other Pacific Islander (NHPI) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.
1990 division of the city into neighborhoods based mostly on neighborhood and housing association boundaries modified to eliminate gaps or overlaps. Census data from 1990 were used for the areas and the demographic statistics have been estimated since then to use the data for graphical and analytical purposes. Several areas with very little population in 1990 were not identified as neighborhoods.
Report on Demographic Data in New York City Public Schools, 2020-21Enrollment counts are based on the November 13 Audited Register for 2020. Categories with total enrollment values of zero were omitted. Pre-K data includes students in 3-K. Data on students with disabilities, English language learners, and student poverty status are as of March 19, 2021. Due to missing demographic information in rare cases and suppression rules, demographic categories do not always add up to total enrollment and/or citywide totals. NYC DOE "Eligible for free or reduced-price lunch” counts are based on the number of students with families who have qualified for free or reduced-price lunch or are eligible for Human Resources Administration (HRA) benefits. English Language Arts and Math state assessment results for students in grade 9 are not available for inclusion in this report, as the spring 2020 exams did not take place. Spring 2021 ELA and Math test results are not included in this report for K-8 students in 2020-21. Due to the COVID-19 pandemic’s complete transformation of New York City’s school system during the 2020-21 school year, and in accordance with New York State guidance, the 2021 ELA and Math assessments were optional for students to take. As a result, 21.6% of students in grades 3-8 took the English assessment in 2021 and 20.5% of students in grades 3-8 took the Math assessment. These participation rates are not representative of New York City students and schools and are not comparable to prior years, so results are not included in this report. Dual Language enrollment includes English Language Learners and non-English Language Learners. Dual Language data are based on data from STARS; as a result, school participation and student enrollment in Dual Language programs may differ from the data in this report. STARS course scheduling and grade management software applications provide a dynamic internal data system for school use; while standard course codes exist, data are not always consistent from school to school. This report does not include enrollment at District 75 & 79 programs. Students enrolled at Young Adult Borough Centers are represented in the 9-12 District data but not the 9-12 School data. “Prior Year” data included in Comparison tabs refers to data from 2019-20. “Year-to-Year Change” data included in Comparison tabs indicates whether the demographics of a school or special program have grown more or less similar to its district or attendance zone (or school, for special programs) since 2019-20. Year-to-year changes must have been at least 1 percentage point to qualify as “More Similar” or “Less Similar”; changes less than 1 percentage point are categorized as “No Change”. The admissions method tab contains information on the admissions methods used for elementary, middle, and high school programs during the Fall 2020 admissions process. Fall 2020 selection criteria are included for all programs with academic screens, including middle and high school programs. Selection criteria data is based on school-reported information. Fall 2020 Diversity in Admissions priorities is included for applicable middle and high school programs. Note that the data on each school’s demographics and performance includes all students of the given subgroup who were enrolled in the school on November 13, 2020. Some of these students may not have been admitted under the admissions method(s) shown, as some students may have enrolled in the school outside the centralized admissions process (via waitlist, over-the-counter, or transfer), and schools may have changed admissions methods over the past few years. Admissions methods are only reported for grades K-12. "3K and Pre-Kindergarten data are reported at the site level. See below for definitions of site types included in this report. Additionally, please note that this report excludes all students at District 75 sites, reflecting slightly lower enrollment than our total of 60,265 students
Statistics Canada publishes monthly labour force statistics for all Canadian Census Metropolitan Areas (CMAs) and provinces. In addition, the City of Toronto purchases a special run from Statistics Canada of Labour Force Survey (LFS) data for city of Toronto residents (i.e. separate from the rest of the Toronto CMA). LFS data are collected by place of residence, and therefore city of Toronto's "employment" represents "employed residents" and not "jobs" in the city of Toronto. There are more jobs in the city of Toronto than employed city of Toronto residents. In this LFS database, you will find 22 monthly tables and 28 annual tables. Most of the tables contain data for five geographies: city of Toronto, Toronto CMA, Toronto/Hamilton/Oshawa CMAs, Ontario and Canada ( see attachment Table of Contents below a full description ). LFS data in the IVT tables are not seasonally adjusted. Top level seasonally adjusted LFS data are available in our monthly Toronto Economic Bulletin on Open Data. LFS is based on a monthly sample of approximately 2,800 households in the Toronto CMA, about half of the sample is from the city of Toronto; therefore, estimates will vary from the results of a complete census. LFS follows a rotating panel sample design, in which households remain in the sample for six consecutive months. The total sample consists of six representative sub-samples of panels, and each month a panel is replaced after completing its six month stay in the survey. Outgoing households are replaced by households in the same or similar area. This results in a five-sixths month-to-month sample overlap, which makes the design efficient for estimating month-to-month changes. The rotation after six months prevents undue respondent burden for households that are selected for the survey ( see attachment Guide to the Labour Force Survey for more information). Upon reviewing the data, you will see that at least some cells in the IVT tables have been suppressed. For confidentiality reasons, Statistics Canada suppresses Labour Force Survey data for any cell that corresponds to less than 1,500 persons. At the beginning of 2015, Statistics Canada substantially changed the methodology used to produce LFS population estimates for the city of Toronto. These changes have resulted in large and inexplicable swings in population and related counts, which are not real. However, the unemployment and participation rates for city residents showed very little change in this revision. The red dots in the chart above represents Statistics Canada's Annual Demographics estimates for the populations of the city of Toronto, age 15 and over. These are only estimates, but they are generally accepted as the most accurate estimates for the city's population. (Source: https://www150.statcan.gc.ca/n1/pub/91-214-x/91-214-x2018000-eng.htm). The most recent Statistics Canada population estimate for the city of Toronto is for July 1, 2015; therefore, we have to use projections thereafter. There are several population projections for the city. The projection that EDC staff has chosen to use for rebasing city of Toronto LFS data is the Ontario Ministry of Finance Population Projections 2017-2041 and downloaded June, 2017 from http://www.fin.gov.on.ca/en/economy/demographics/projections/ Please see attachment Rebased Labour Force Survey for City of Toronto below for annual adjustment factors, monthly adjustment factors and an example of how to rebase the absolute numbers for the city of Toronto.
https://www.florida-demographics.com/terms_and_conditionshttps://www.florida-demographics.com/terms_and_conditions
A dataset listing Florida cities by population for 2024.
https://www.oklahoma-demographics.com/terms_and_conditionshttps://www.oklahoma-demographics.com/terms_and_conditions
A dataset listing Oklahoma cities by population for 2024.
Families of tax filers; Census families with children by age of children and children by age groups (final T1 Family File; T1FF).
The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.
The report contains thirteen (13) performance metrics for City's workforce development programs. Each metric can be breakdown by three demographic types (gender, race/ethnicity, and age group) and the program target population (e.g., youth and young adults, NYCHA communities) as well. This report is a key output of an integrated data system that collects, integrates, and generates disaggregated data by Mayor's Office for Economic Opportunity (NYC Opportunity). Currently, the report is generated by the integrated database incorporating data from 18 workforce development programs managed by 5 City agencies. There has been no single "workforce development system" in the City of New York. Instead, many discrete public agencies directly manage or fund local partners to deliver a range of different services, sometimes tailored to specific populations. As a result, program data have historically been fragmented as well, making it challenging to develop insights based on a comprehensive picture. To overcome it, NYC Opportunity collects data from 5 City agencies and builds the integrated database, and it begins to build a complete picture of how participants move through the system onto a career pathway. Each row represents a count of unique individuals for a specific performance metric, program target population, a specific demographic group, and a specific period. For example, if the Metric Value is 2000 with Clients Served (Metric Name), NYCHA Communities (Program Target Population), Asian (Subgroup), and 2019 (Period), you can say that "In 2019, 2,000 Asian individuals participated programs targeting NYCHA communities. Please refer to the Workforce Data Portal for further data guidance (https://workforcedata.nyc.gov/en/data-guidance), and interactive visualizations for this report (https://workforcedata.nyc.gov/en/common-metrics).
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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Insight Factsheets The following factsheets can be found here:
Birmingham Community Safety
This factsheet provides key insights from the Birmingham Community Safety Dashboard which supports the Serious Violence Strategic Needs Assessment. It provides a comprehensive understanding of crimes reported in Birmingham, including breakdowns by crime categories and demographics of suspects, victims and vulnerable groups who may be subject to violence or harm.
Climate Change Briefing Book
The Climate Change Briefing Book dashboard provides a wealth of data regarding key topics such as emissions, homes and energy performance, transportation, refuse, recycling and waste disposal and environmental justice. The dashboard provides an insight into climate-related topics within Birmingham and how as a city, it compares to other geographical areas such as the English Core Cities.
Economy briefing for Leader This factsheet provides information on the latest economic statistics in Birmingham.
Housing Briefing Book for publishing
The Housing Briefing Book brings together data that is internally held, as well as external sources to provide a rich understanding of the housing stock in Birmingham. The dashboard provides information on all dwellings in Birmingham, council owned housing stock, social housing lettings, rooms, tenure, housing supply, affordability and benefits, and Help to Buy.
Inequality in Birmingham Headline Statistics
This document provides a comprehensive statistical overview of various socio-economic factors affecting Birmingham, highlighting the disparities in education, income, health, and housing among different demographics.
Post 16 Employment and Skills for publishing
The Post-16 Employment & Skills dashboard brings together data that is internally held by the council, as well as external sources, to provide information on the following themes:
1) Young People: Population composition and projections of young people in the city 2) Supply: The destinations of young people in terms of education, employment and/or training 3) Demand: Labour market trends, and 4) Provider: Distance travelled by young people in Birmingham to a learning provider.
SEND Briefing Book
The SEND Briefing Book dashboard provides an overview of people with special educational needs and disabilities (SEND) in Birmingham. In order to learn and have the same opportunities as all children, those with SEND require educational provision that is additional to, or different from, that made generally for others of the same age.
Viewing and downloading This dataset contains unstructured files such as documents, PDF's and images.
To view and download the files click on the Table tab at the top and select the desired file in the File name column.
You may use the filters to further refine your selection.
ℹ️
Note
The Export and
API will only download the table of contents.
Assessment of the dangers from AIDS. Attitude to the social consequences of AIDS. Topics: 1. as oral survey: degree of urbanization of place of residence; general assessment of dangers and temptations for young people in large cities; assessment of the danger of AIDS infection in large cities; expected risk of crime in Germany in the extent of American cities; probability of future personal isolation due to AIDS; assessment of current and future social menace from AIDS; general attitude to the handicapped and illnesses as well as perceived feeling of threat from AIDS and readiness for risk (scale); personal ideas on AIDS prevention; centrality of the illness AIDS in the ideas of respondent in comparison to other illness risks; dealing with AIDS and assignment of blame to fringe groups (scale); perceived threat from AIDS in one´s family and circle of friends; influence of AIDS on daily behavior with people as well as feeling of safety; dealing with AIDS patients or isolation (scale); state of knowledge about possibilities of infection with AIDS; state of knowledge about the number of AIDS-infected people in Germany; active or casual gathering of information on AIDS; assessment of danger of AIDS-infection in selected situations in daily life; attitude to selected statements on social as well as personal dealing with AIDS (scale); governmental or personal responsibility for protection from AIDS and assumed attitude of the population on this question; compulsory measures or education as promising measure to contain AIDS as well as assumed attitude of the population on this question; attitude to compulsory registration, to entry prohibition for AIDS-infected people as well as compulsory tests for main risk groups or for everyone as well as assumed attitude of the population on this question; government, health insurance companies or those impacted themselves as bearers of the costs for care of AIDS patients; willingness to pay higher health insurance fees for care of AIDS-infected people and AIDS patients; attitude to a special AIDS tax for everyone; preferred compulsory measures to protect the healthy against AIDS-infected people (scale) and assumed view of the population on these questions; preference for privacy protection for AIDS patients or protection of the healthy at the cost of AIDS-infected people; assumed general overestimate or underestimate of the AIDS danger in Germany. 2. As written form to be filled out the respondent answered the following: AIDS-infected people in one´s circle of friends; perceived certainty currently and in the future of respondent´s not being infected with AIDS; promiscuity and marital fidelity (scale); information on sexual behavior in the last 12 months with changing partners and random acquaintances; consciousness of the danger of AIDS infection and considerations for protection; condom use; attitude to condom use in future relations with unknown partners. 3. Demography: sex; age in years; school education; vocational training; employment; occupational position; marital status; self-assessment of social class; religious denomination; religiousness; party preference; income; size of household; composition of household; household income; telephone; possession of telephone answering device. Einschätzung der Gefahren durch AIDS. Einstellung zu den gesellschaftlichen Folgen von AIDS. Themen: 1. Als mündliche Befragung: Urbanisierungsgrad des Wohnortes; allgemeine Einschätzung der Gefahren und Versuchungen junger Menschen in Großstädten; Einschätzung der AIDS-Ansteckungsgefahr in großen Städten; erwartete Kriminalitätsgefährdung in Deutschland im Ausmaß von amerikanischen Städten; Wahrscheinlichkeit einer zukünftigen persönlichen Abschottung wegen AIDS; Einschätzung einer gegenwärtigen und zukünftigen gesellschaftlichen Bedrohung durch AIDS; allgemeine Einstellung zu Behinderten und Krankheiten sowie empfundenes Bedrohtheitsgefühl durch AIDS und Risikobereitschaft (Skala); persönliche Vorstellungen zur AIDS-Prävention; Zentralität der Krankheit AIDS in den Vorstellungen des Befragten im Vergleich zu übrigen Krankheitsrisiken; Umgang mit AIDS und Schuldzuschreibung zu Randgruppen (Skala); empfundene Bedrohung durch AIDS im eigenen Familien- und Freundeskreis; Einfluß von AIDS auf den täglichen Umgang mit Menschen sowie Sicherheitsempfinden; Umgang mit AIDS-Kranken oder Ausgrenzung (Skala); Kenntnisstand über Ansteckungsmöglichkeiten mit AIDS; Kenntnisstand über die Anzahl der AIDS-Infizierten in Deutschland; aktive oder beiläufige Informationsbeschaffung über AIDS; Einschätzung der Ansteckungsgefahr mit AIDS in ausgewählten Alltagssituationen; Einstellung zu ausgewählten Aussagen zum gesellschaftlichen wie auch persönlichen Umgang mit AIDS (Skala); staatliche oder persönliche Verantwortung für den Schutz vor AIDS und vermutete Einstellung der Bevölkerung in dieser Frage; Zwangsmaßnahmen oder Aufklärung als erfolgsversprechende Maßnahme zur Eindämmung von AIDS sowie vermutete Einstellung der Bevölkerung in dieser Frage; Einstellung zur Meldepflicht, zu Einreiseverboten von AIDS-Infizierten sowie Zwangstests für die Hauptrisikogruppen bzw. für alle sowie vermutete Einstellung der Bevölkerung in dieser Frage; Staat, Krankenkassen oder die betroffenen selbst als Kostenträger für die Betreuung von AIDS-Kranken; Bereitschaft zur Zahlung höherer Krankenkassenbeiträge zur Betreuung von AIDS-Infizierten und AIDS-Kranken; Einstellung zu einer AIDS-Sonderabgabe für alle; präferierte Zwangsmaßnahmen zum Schutz von Gesunden vor AIDS-Infizierten (Skala) und vermutete Ansicht der Bevölkerung zu diesen Fragen; Präferenz für Persönlichkeitsschutz der AIDS-Kranken oder Schutz der Gesunden auf Kosten der AIDS-Infizierten; vermutete allgemeine Überschätzung bzw. Unterschätzung der AIDS-Gefahr in Deutschland. 2. Als schriftlicher Selbstausfüller wurde vom Befragten beantwortet: AIDS-Infizierte im Bekanntenkreis; empfundene Sicherheit der gegenwärtigen und zukünftigen Nichtansteckung des Befragten mit AIDS; Promiskuität und eheliche Treue (Skala); Angaben über das Sexualverhalten in den letzten 12 Monaten mit wechselnden Partnern und Zufallsbekanntschaften; Bewußtsein der Gefahr einer AIDS-Ansteckung und Schutzüberlegungen; Kondombenutzung; Einstellung zur Kondombenutzung bei zukünftigen Beziehungen zu unbekannten Partnern. 3. Demographie: Geschlecht; Alter in Jahren; Schulbildung; Berufsausbildung; Berufstätigkeit; berufliche Position; Familienstand; Selbsteinschätzung der Schichtzugehörigkeit; Konfession; Religiosität; Parteipräferenz; Einkommen; Haushaltsgröße; Haushaltszusammensetzung; Haushaltseinkommen; Telefonanschluß; Besitz eines Anrufbeantworters.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 3 cities in the Young County, TX by Non-Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.