About this dataset

Context

The dataset tabulates the Black Earth population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Black Earth across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Black Earth was 1,448, a 0.34% decrease year-by-year from 2022. Previously, in 2022, Black Earth population was 1,453, a decline of 1.29% compared to a population of 1,472 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Black Earth increased by 122. In this period, the peak population was 1,494 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Black Earth is shown in this column.
• Year on Year Change: This column displays the change in Black Earth population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Black Earth Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of United States by race. It includes the distribution of the Non-Hispanic population of United States across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of United States across relevant racial categories.

Key observations

Of the Non-Hispanic population in United States, the largest racial group is White alone with a population of 194.89 million (72.36% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the United States
• Population: The population of the racial category (for Non-Hispanic) in the United States is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of United States total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for United States Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Lynch by race. It includes the population of Lynch across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Lynch across relevant racial categories.

Key observations

The percent distribution of Lynch population by race (across all racial categories recognized by the U.S. Census Bureau): 95.86% are white, 1.18% are some other race and 2.96% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Lynch
• Population: The population of the racial category (excluding ethnicity) in the Lynch is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Lynch total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Lynch Population by Race & Ethnicity. You can refer the same here

Key Table Information.Table Title.Vintage 2023 Annual Resident Population Estimates by Selected Age Groups and Sex: April 1, 2020 to July 1, 2023.Table ID.PEPCHARV2023.PEP_AGESEX.Survey/Program.Population Estimates.Year.2023.Dataset.PEP Demographic Characteristics.Source.U.S. Census Bureau, 2023 Population Estimates.Release Date.June 2024.Methodology.Geography Coverage.All geographic boundaries for the 2023 population estimates series are as of January 1, 2023. Substantial geographic changes to counties can be found on the Census Bureau website at https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.html.Confidentiality.Vintage 2023 data products are associated with Data Management System projects P6000042, P-7501659, and P-7527355. The U.S. Census Bureau reviewed these data products for unauthorized disclosure of confidential information and approved the disclosure avoidance practices applied to this release (CBDRB-FY24-0085)..Technical Documentation/Methodology.The estimates are developed from a base that integrates the 2020 Census, Vintage 2020 estimates, and 2020 Demographic Analysis estimates. The estimates add births to, subtract deaths from, and add net migration to the April 1, 2020 estimates base. Race data in the Vintage 2023 estimates do not currently reflect the results of the 2020 Census. For population estimates methodology statements, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html.'In combination' means in combination with one or more other races. The sum of the five race groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of Some Other Race from the decennial census are modified to be consistent with the race categories that appear in our input data. This contributes to differences between the population for specific race categories shown and those published from the 2020 Census. To learn more about the Modified Race process, go to http://www.census.gov/programs-surveys/popest/technical-documentation/research/modified-race-data.html..Weights.Data is not weighted.Table Information.FTP Download.https://www2.census.gov/programs-surveys/popest/.Additional Information.Contact Information.pop.cdob@census.gov.Suggested Citation.U.S. Census Bureau. "Vintage 2023 Annual Resident Population Estimates by Selected Age Groups and Sex: April 1, 2020 to July 1, 2023" Population Estimates, PEP Demographic Characteristics, Table PEP_AGESEX, -1, https://data.census.gov/table/PEPCHARV2023.PEP_AGESEX?q=PEP_AGESEX: Accessed on June 18, 2025..

In 2022, there were 313,017 cases filed by the NCIC where the race of the reported missing was White. In the same year, 18,928 people were missing whose race was unknown.

What is the NCIC?

The National Crime Information Center (NCIC) is a digital database that stores crime data for the United States, so criminal justice agencies can access it. As a part of the FBI, it helps criminal justice professionals find criminals, missing people, stolen property, and terrorists. The NCIC database is broken down into 21 files. Seven files belong to stolen property and items, and 14 belong to persons, including the National Sex Offender Register, Missing Person, and Identify Theft. It works alongside federal, tribal, state, and local agencies. The NCIC’s goal is to maintain a centralized information system between local branches and offices, so information is easily accessible nationwide.

Missing people in the United States

A person is considered missing when they have disappeared and their location is unknown. A person who is considered missing might have left voluntarily, but that is not always the case. The number of the NCIC unidentified person files in the United States has fluctuated since 1990, and in 2022, there were slightly more NCIC missing person files for males as compared to females. Fortunately, the number of NCIC missing person files has been mostly decreasing since 1998.

About this dataset

Context

The dataset tabulates the population of Gay by race. It includes the population of Gay across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Gay across relevant racial categories.

Key observations

The percent distribution of Gay population by race (across all racial categories recognized by the U.S. Census Bureau): 87.70% are white, 11.48% are some other race and 0.82% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Gay
• Population: The population of the racial category (excluding ethnicity) in the Gay is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Gay total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Gay Population by Race & Ethnicity. You can refer the same here

United States Employment: sa: NH: Black or African American: Female data was reported at 10,591.000 Person th in Apr 2025. This records a decrease from the previous number of 10,672.000 Person th for Mar 2025. United States Employment: sa: NH: Black or African American: Female data is updated monthly, averaging 7,702.000 Person th from Jan 1972 (Median) to Apr 2025, with 640 observations. The data reached an all-time high of 10,917.000 Person th in Feb 2024 and a record low of 3,391.000 Person th in Feb 1972. United States Employment: sa: NH: Black or African American: Female data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Population Survey: Employment: Seasonally Adjusted.

Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data.

CDC has three COVID-19 case surveillance datasets:

• COVID-19 Case Surveillance Public Use Data with Geography: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements)
• COVID-19 Case Surveillance Public Use Data: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements)
• COVID-19 Case Surveillance Restricted Access Detailed Data: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (33 data elements)

• Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
• Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.
• Some data cells are suppressed to protect individual privacy.
• The datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured.
• Datasets are updated monthly.
• Datasets are created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy.
• For more information about data collection and reporting, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
• For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html
  

Overview

The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (Interim-20-ID-01). CSTE updated the position statement on August 5, 2020, to clarify the interpretation of antigen detection tests and serologic test results within the case classification (Interim-20-ID-02). The statement also recommended that all states and territories enact laws to make COVID-19 reportable in their jurisdiction, and that jurisdictions conducting surveillance should submit case notifications to CDC. COVID-19 case surveillance data are collected by jurisdictions and reported voluntarily to CDC.

For more information: NNDSS Supports the COVID-19 Response | CDC.

The deidentified data in the “COVID-19 Case Surveillance Public Use Data” include demographic characteristics, any exposure history, disease severity indicators and outcomes, clinical data, laboratory diagnostic test results, and presence of any underlying medical conditions and risk behaviors. All data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.

COVID-19 Case Reports

COVID-19 case reports have been routinely submitted using nationally standardized case reporting forms. On April 5, 2020, CSTE released an Interim Position Statement with national surveillance case definitions for COVID-19 included. Current versions of these case definitions are available here: https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-2021/.

All cases reported on or after were requested to be shared by public health departments to CDC using the standardized case definitions for laboratory-confirmed or probable cases. On May 5, 2020, the standardized case reporting form was revised. Case reporting using this new form is ongoing among U.S. states and territories.

Data are Considered Provisional

• The COVID-19 case surveillance data are dynamic; case reports can be modified at any time by the jurisdictions sharing COVID-19 data with CDC. CDC may update prior cases shared with CDC based on any updated information from jurisdictions. For instance, as new information is gathered about previously reported cases, health departments provide updated data to CDC. As more information and data become available, analyses might find changes in surveillance data and trends during a previously reported time window. Data may also be shared late with CDC due to the volume of COVID-19 cases.
• Annual finalized data: To create the final NNDSS data used in the annual tables, CDC works carefully with the reporting jurisdictions to reconcile the data received during the year until each state or territorial epidemiologist confirms that the data from their area are correct.
• Access Addressing Gaps in Public Health Reporting of Race and Ethnicity for COVID-19, a report from the Council of State and Territorial Epidemiologists, to better understand the challenges in completing race and ethnicity data for COVID-19 and recommendations for improvement.

Data Limitations

To learn more about the limitations in using case surveillance data, visit FAQ: COVID-19 Data and Surveillance.

Data Quality Assurance Procedures

CDC’s Case Surveillance Section routinely performs data quality assurance procedures (i.e., ongoing corrections and logic checks to address data errors). To date, the following data cleaning steps have been implemented:

• Questions that have been left unanswered (blank) on the case report form are reclassified to a Missing value, if applicable to the question. For example, in the question “Was the individual hospitalized?” where the possible answer choices include “Yes,” “No,” or “Unknown,” the blank value is recoded to Missing because the case report form did not include a response to the question.
• Logic checks are performed for date data. If an illogical date has been provided, CDC reviews the data with the reporting jurisdiction. For example, if a symptom onset date in the future is reported to CDC, this value is set to null until the reporting jurisdiction updates the date appropriately.
• Additional data quality processing to recode free text data is ongoing. Data on symptoms, race and ethnicity, and healthcare worker status have been prioritized.

Data Suppression

To prevent release of data that could be used to identify people, data cells are suppressed for low frequency (<5) records and indirect identifiers (e.g., date of first positive specimen). Suppression includes rare combinations of demographic characteristics (sex, age group, race/ethnicity). Suppressed values are re-coded to the NA answer option; records with data suppression are never removed.

For questions, please contact Ask SRRG (eocevent394@cdc.gov).

Additional COVID-19 Data

COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths by state and by county. These

Key Table Information.Table Title.Vintage 2023 Annual Resident Population Estimates by Age, Sex, Race, and Hispanic Origin: April 1, 2020 to July 1, 2023.Table ID.PEPCHARV2023.PEP_ALLDATA.Survey/Program.Population Estimates.Year.2023.Dataset.PEP Demographic Characteristics.Source.U.S. Census Bureau, 2023 Population Estimates.Release Date.June 2024.Methodology.Geography Coverage.All geographic boundaries for the 2023 population estimates series are as of January 1, 2023. Substantial geographic changes to counties can be found on the Census Bureau website at https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.html.Confidentiality.Vintage 2023 data products are associated with Data Management System projects P6000042, P-7501659, and P-7527355. The U.S. Census Bureau reviewed these data products for unauthorized disclosure of confidential information and approved the disclosure avoidance practices applied to this release (CBDRB-FY24-0085)..Technical Documentation/Methodology.The estimates are developed from a base that integrates the 2020 Census, Vintage 2020 estimates, and 2020 Demographic Analysis estimates. The estimates add births to, subtract deaths from, and add net migration to the April 1, 2020 estimates base. Race data in the Vintage 2023 estimates do not currently reflect the results of the 2020 Census. For population estimates methodology statements, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html.'In combination' means in combination with one or more other races. The sum of the five race groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of Some Other Race from the decennial census are modified to be consistent with the race categories that appear in our input data. This contributes to differences between the population for specific race categories shown and those published from the 2020 Census. To learn more about the Modified Race process, go to http://www.census.gov/programs-surveys/popest/technical-documentation/research/modified-race-data.html..Weights.Data is not weighted.Table Information.FTP Download.https://www2.census.gov/programs-surveys/popest/.Additional Information.Contact Information.pop.cdob@census.gov.Suggested Citation.U.S. Census Bureau. "Vintage 2023 Annual Resident Population Estimates by Age, Sex, Race, and Hispanic Origin: April 1, 2020 to July 1, 2023" Population Estimates, PEP Demographic Characteristics, Table PEP_ALLDATA, -1, https://data.census.gov/table/PEPCHARV2023.PEP_ALLDATA?q=PEP_ALLDATA: Accessed on June 06, 2025..

2014 - 2022 (excluding 2020). This dataset is a de-identified summary table of vision and eye health data indicators from ACS, stratified by all available combinations of age group, race/ethnicity, gender, and state. ACS is an annual nationwide survey conducted by the U.S. Census Bureau that collects information on demographic, social, economic, and housing characteristics of the U.S. population. Approximate sample size is 3 million annually. ACS data for VEHSS includes one question related to Visual Function. Data were suppressed for cell sizes less than 30 persons, or where the relative standard error more than 30% of the mean. Data will be updated as it becomes available. Detailed information on VEHSS ACS analyses can be found on the VEHSS ACS webpage (link). Additional information about ACS can be found on the U.S. Census Bureau website (https://www.census.gov/content/dam/Census/programs-surveys/acs/about/ACS_Information_Guide.pdf). The VEHSS ACS dataset was last updated April 2024

For those interested in data on student drug addiction in 2024, several sources offer valuable datasets and statistics.

1. Kaggle Dataset: Kaggle hosts a specific dataset on student drug addiction. This dataset includes various attributes related to student demographics, substance use patterns, and associated behavioral factors. It's a useful resource for data analysis and machine learning projects focused on understanding drug addiction among students【5†source】.

2. National Survey on Drug Use and Health (NSDUH): This comprehensive survey provides detailed annual data on substance use and mental health across the United States, including among students. It covers a wide range of substances and demographic details, helping to track trends and the need for treatment services【6†source】【8†source】.

3. Monitoring the Future (MTF) Survey: Conducted by the National Institute on Drug Abuse (NIDA), this survey tracks drug and alcohol use and attitudes among American adolescents. It provides annual updates and is an excellent source for understanding trends in substance use among high school and college students【7†source】.

4. Australian Institute of Health and Welfare (AIHW): For those interested in a more global perspective, the AIHW offers data from the National Drug Strategy Household Survey, which includes information on youth and young adult drug use in Australia. This can be useful for comparative studies【10†source】.

For detailed datasets and further analysis, you can explore these resources directly:

• Kaggle Student Drugs Addiction Dataset
• NSDUH Data
• Monitoring the Future
• AIHW Drug Survey

About this dataset

Context

The dataset tabulates the population of Faith by race. It includes the population of Faith across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Faith across relevant racial categories.

Key observations

The percent distribution of Faith population by race (across all racial categories recognized by the U.S. Census Bureau): 97.04% are white and 2.96% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Faith
• Population: The population of the racial category (excluding ethnicity) in the Faith is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Faith total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Faith Population by Race & Ethnicity. You can refer the same here

Types of Abuse, Neglect and Financial Exploitation - A single APS case can have more than one allegation. Neglect is the failure to provide the protection, food, shelter, or care necessary to avoid emotional harm or physical injury. The alleged perpetrator of the neglect may be the victim or the victim's caregiver. There are three types of neglect allegations: Physical Neglect, Medical Neglect, and Mental Health Neglect. Other allegation types include: Financial Exploitation, Physical Abuse, Emotional or Verbal Abuse, or Sexual Abuse. The population totals do not match prior DFPS Data Books, printed or ontline. 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 will 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 for all years from 2014 to 2023 as of December 2023. Visit dfps.state.tx.us for information on all DFPS programs.

Vintage 2024 Population projections by race, sex and age group for North Carolina counties. Includes population by race (American Indian/Alaska Native), Asian & Pacific Islander (Asian), Black, White, Other (includes persons identified as two or more races). In some counties not all race groups will be reported separately. For population of less than 250 for any race group, the population by age will be reported within the other category and the "group n" for the other category show a number larger than 1 indicating that the other category includes population from other race groups that are separately reported for other counties. For this reason, users should take care in aggregating race group population across counties.

The number of social media users in the United States was forecast to continuously increase between 2024 and 2029 by in total 26 million users (+8.55 percent). After the ninth consecutive increasing year, the social media user base is estimated to reach 330.07 million users and therefore a new peak in 2029. Notably, the number of social media users of was continuously increasing over the past years.The shown figures regarding social media users have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

This study features Supplemental Nutrition Assistance Program (SNAP) policy and enrollment data organized in three datasets. The data were originally collected for a companion paper, Pukelis, K. (2024). "SNAP Policies and Enrollment following the COVID-19 Pandemic." The SNAP COVID Policy Data (DS1) provides monthly data on states' adoption of policies to adjust SNAP enrollment requirements and benefits during the COVID-19 federal public health emergency, from March 2020 through June 2023. This dataset features information from all 50 states regarding policy waivers that were requested to simplify SNAP application and recertification requirements, temporarily waive recertification requirements, and provide emergency supplemental benefits. SNAP implementation procedures data from 2019 are also available for comparison. The SNAP County Enrollment Data (DS2) contains county-month level data on SNAP enrollment numbers, total benefits issued, applications, and recertifications, as well as a handful of measures on the Temporary Assistance for Needy Families (TANF) program and Medicaid. The SNAP State Enrollment Detail Data (DS3) includes state-month level data on SNAP enrollment details, including applications, recertifications, enrollment by demographic group, and information about office walk-in visits and calls to the assistance line. TANF and Medicaid state-month level data is also provided. The state enrollment file also features 62 variables detailing Louisiana case closures. County and state enrollment files contain demographic information for a limited number of states, including SNAP, TANF, and Medicaid enrollment by age group, and state-month SNAP enrollment by gender, race, and ethnicity.

About this dataset

Context

The dataset tabulates the population of State Line by race. It includes the population of State Line across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of State Line across relevant racial categories.

Key observations

The percent distribution of State Line population by race (across all racial categories recognized by the U.S. Census Bureau): 100% are white.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the State Line
• Population: The population of the racial category (excluding ethnicity) in the State Line is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of State Line total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for State Line Population by Race & Ethnicity. You can refer the same here

The National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated school district boundary composite files that include public elementary, secondary, unified, and administrative school district boundaries clipped to the U.S. shoreline. School districts are single-purpose administrative units designed by state and local officials to organize and provide public education for local residents. District boundaries are collected for NCES by the U.S. Census Bureau to support educational research and program administration, and the boundaries are essential for constructing district-level estimates of the number of children in poverty. The Census Bureau’s School District Boundary Review program (SDBR) (https://www.census.gov/programs-surveys/sdrp.html) obtains the boundaries, names, and grade ranges from state officials, and integrates these updates into Census TIGER. Census TIGER boundaries include legal maritime buffers for coastal areas by default, but the NCES composite file removes these buffers to facilitate broader use and cleaner cartographic representation. The NCES EDGE program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to develop the composite school district files. The inputs for this data layer were developed from Census TIGER/Line 2022 and represent boundaries reported for the 2021-2022 school year. For more information about NCES school district boundary data, see https://nces.ed.gov/programs/edge/Geographic/DistrictBoundaries. All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data

About this dataset

Context

The dataset tabulates the Black Brook town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Black Brook town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Black Brook town was 1,462, a 0.76% increase year-by-year from 2022. Previously, in 2022, Black Brook town population was 1,451, an increase of 0.48% compared to a population of 1,444 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Black Brook town increased by 258. In this period, the peak population was 1,462 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Black Brook town is shown in this column.
• Year on Year Change: This column displays the change in Black Brook town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Black Brook town Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the population of State Line City by race. It includes the population of State Line City across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of State Line City across relevant racial categories.

Key observations

The percent distribution of State Line City population by race (across all racial categories recognized by the U.S. Census Bureau): 94.29% are white, 2.14% are Black or African American and 3.57% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the State Line City
• Population: The population of the racial category (excluding ethnicity) in the State Line City is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of State Line City total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for State Line City Population by Race & Ethnicity. You can refer the same here