The population rate of change of Allen, TX was 2.47% in 2018.

Population

Population Change

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

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Demographics and Population Datasets Involving Allen, TX

  • API

    CPI 1.1 Texas Child Population (ages 0-17) by County 2014-2023

    data.texas.gov | Last Updated 2024-09-05T21:23:24.000Z

    As recommended by the Health and Human Services Commission (HHSC) to ensure consistency across all HHSC agencies, in 2012 DFPS adopted the HHSC methodology on how to categorize race and ethnicity. As a result, data broken down by race and ethnicity in 2012 and after is not directly comparable to race and ethnicity data in 2011 and before. The population totals may not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Children, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections data as of December 2020. Visit dfps.texas.gov for information on all DFPS programs.

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    NYCHA Resident Data Book Summary

    data.cityofnewyork.us | Last Updated 2020-02-08T00:56:30.000Z

    Contains resident demographic data at a summary level as of January 1, 2019. The Resident Data Book is compiled to serve as an information source for queries involving resident demographic as well as a source of data for internal analysis. Statistics are compiled via HUD mandated annual income reviews involving NYCHA Staff and residents. Data is then aggregated and compiled by development. Each record pertains to a single public housing development.

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    APS 1.1 Texas Adult Populations at Risk by County/Region FY2014-FY2023

    data.texas.gov | Last Updated 2024-02-06T21:20:23.000Z

    APS investigates allegations of abuse, neglect, and financial exploitation and provides protective services, regardless of race, creed, color, or national origin to people who are: • age 65 or older; • age 18-64 with a mental, physical, or developmental disability that substantially impairs the ability to live independently or provide for their own self-care or protection; or • emancipated minors with a mental, physical, or developmental disability that substantially impairs the ability to live independently or provide for their own self-care or protection. APS clients do not have to meet financial eligibility requirements. The population totals will not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Population, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections for all years from 2010 to 2019 as of December 2019.

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    CPS 2.1 Removals - by Region with Child Demographics FY2014-2023

    data.texas.gov | Last Updated 2024-02-12T17:52:15.000Z

    A removal occurs when CPS determines that a child cannot safely remain in their own home and that DFPS needs to seek legal custody to ensure child safety. Removals can occur in an investigation, family preservation, family substitute care or family reunification stage. Visit dfps.texas.gov for information on CPS Abuse/Neglect Investigations and all DFPS programs.

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    Bronx Zip Population and Density

    bronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z

    2010 Census Data on population, pop density, age and ethnicity per zip code

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    CPI 3.8 Abuse/Neglect Investigations - Victims with Demographics by Region FY2014-FY2023

    data.texas.gov | Last Updated 2024-01-30T18:53:54.000Z

    This chart counts victims in completed investigations. Completed investigations only include those cases conducted as a traditional investigation that were not administratively closed or merged into another stage. An investigation can only be administratively closed if all allegations have a disposition of administrative closure. A completed investigation can include more than one alleged victim. Completed investigations do not include any Alternative Response stages. A confirmed victim on a completed investigation is a child who is a victim on at least one allegation with a disposition of reason to believe. An unconfirmed victim on a completed investigation is a child who was an alleged victim on at least one allegation with a disposition of unable to complete, unable to determine or ruled out. A description of Alternative Response and how it differs from a traditional investigation and the definitions of the different dispositions in a traditional investigation are in the glossary. Visit dfps.texas.gov for information on CPS Abuse/Neglect Investigations and all DFPS programs.

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    Demographics Stats at a Glance

    datahub.austintexas.gov | Last Updated 2024-10-24T14:56:11.000Z

    These are the statistics listed in the "Stats at a Glance" section of the City of Austin demographics website: https://demographics-austin.hub.arcgis.com/

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    NYSERDA Low- to Moderate-Income New York State Census Population Analysis Dataset: Average for 2013-2015

    data.ny.gov | Last Updated 2019-11-15T22:30:02.000Z

    How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015. Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population. The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight. The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).

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    Indicators of Anxiety or Depression Based on Reported Frequency of Symptoms During Last 7 Days

    data.cdc.gov | Last Updated 2024-10-04T14:06:38.000Z

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness. The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, gender, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions,

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    City of Austin Displacement Risk Areas 2020

    datahub.austintexas.gov | Last Updated 2024-07-09T18:23:48.000Z

    To determine displacement risk, researchers at the University of Texas conducted a three-part analysis: the presence of vulnerable populations, residential market appreciation, and demographic change. To determine vulnerable populations, the authors used indicators to identify residents who, according to academic research, are least able to absorb housing costs, which includes: communities of color, low-income households, heads of households without a bachelor's degree or higher, families with children in poverty, and renters. In 2019 and 2020, the City of Austin Housing and Planning staff updated the data and simplified the categories below. Vulnerable: Vulnerable populations present, no significant demographic change, some tracts are near or contain high-value and high-appreciation areas. Active Displacement Risk: Vulnerable populations present, active demographic change, accelerating or appreciating housing market. Chronic Displacement Risk: Vulnerable populations have been displaced, demographic change has occurred and the housing market is high value and appreciated or appreciating. Historic Displacement: Tracts previously identified as at-risk to displacement in earlier Uprooted models (2016, 2019)