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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The dataset tabulates the population of Federal Way by race. It includes the population of Federal Way across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Federal Way across relevant racial categories.
Key observations
The percent distribution of Federal Way population by race (across all racial categories recognized by the U.S. Census Bureau): 38.79% are white, 17.80% are Black or African American, 0.88% are American Indian and Alaska Native, 14.51% are Asian, 3.22% are Native Hawaiian and other Pacific Islander, 10.17% are some other race and 14.63% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Federal Way Population by Race & Ethnicity. You can refer the same here
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TwitterThe dataset contains estimates for the number of healthcare professionals in 15 different healthcare categories (e.g., Registered Nurse, Dentist, License Clinical Social Worker, etc.) based on completion of license renewal by Race/Ethnicity. There are two timeframes: all current licenses and recent licenses (since 2017). California population estimates are also included to provide a marker for each Race/Ethnicity. Each healthcare professional category can be compared across Race/Ethnicity groups and compared to statewide population estimates, so Race/Ethnicity shortages can be identified for each healthcare professional category. For instance, a notable difference between healthcare professional category and statewide population would indicate either underrepresentation or overrepresentation for that Race/Ethnicity, depending on the direction of the difference.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The dataset tabulates the population of Burlington by race. It includes the population of Burlington across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Burlington across relevant racial categories.
Key observations
The percent distribution of Burlington population by race (across all racial categories recognized by the U.S. Census Bureau): 95.36% are white, 1.32% are Black or African American, 0.66% are American Indian and Alaska Native and 2.65% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Burlington Population by Race & Ethnicity. You can refer the same here
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TwitterODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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A. SUMMARY This dataset includes San Francisco COVID-19 tests by race/ethnicity and by date. This dataset represents the daily count of tests collected, and the breakdown of test results (positive, negative, or indeterminate). Tests in this dataset include all those collected from persons who listed San Francisco as their home address at the time of testing. It also includes tests that were collected by San Francisco providers for persons who were missing a locating address. This dataset does not include tests for residents listing a locating address outside of San Francisco, even if they were tested in San Francisco.
The data were de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected). If a person tested multiple times on the same date, only one test is included from that date. When there are multiple tests on the same date, a positive result, if one exists, will always be selected as the record for the person. If a PCR and antigen test are taken on the same day, the PCR test will supersede. If a person tests multiple times on the same day and the results are all the same (e.g. all negative or all positive) then the first test done is selected as the record for the person.
The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco.
When a person gets tested for COVID-19, they may be asked to report information about themselves. One piece of information that might be requested is a person's race and ethnicity. These data are often incomplete in the laboratory and provider reports of the test results sent to the health department. The data can be missing or incomplete for several possible reasons:
• The person was not asked about their race and ethnicity.
• The person was asked, but refused to answer.
• The person answered, but the testing provider did not include the person's answers in the reports.
• The testing provider reported the person's answers in a format that could not be used by the health department.
For any of these reasons, a person's race/ethnicity will be recorded in the dataset as “Unknown.”
B. NOTE ON RACE/ETHNICITY The different values for Race/Ethnicity in this dataset are "Asian;" "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" "White;" "Multi-racial;" "Other;" and “Unknown."
The Race/Ethnicity categorization increases data clarity by emulating the methodology used by the U.S. Census in the American Community Survey. Specifically, persons who identify as "Asian," "Black or African American," "American Indian or Alaska Native," "Native Hawaiian or Other Pacific Islander," "White," "Multi-racial," or "Other" do NOT include any person who identified as Hispanic/Latino at any time in their testing reports that either (1) identified them as SF residents or (2) as someone who tested without a locating address by an SF provider. All persons across all races who identify as Hispanic/Latino are recorded as “"Hispanic or Latino/a, all races." This categorization increases data accuracy by correcting the way “Other” persons were counted. Previously, when a person reported “Other” for Race/Ethnicity, they would be recorded “Unknown.” Under the new categorization, they are counted as “Other” and are distinct from “Unknown.”
If a person records their race/ethnicity as “Asian,” “Black or African American,” “American Indian or Alaska Native,” “Native Hawaiian or Other Pacific Islander,” “White,” or “Other” for their first COVID-19 test, then this data will not change—even if a different race/ethnicity is reported for this person for any future COVID-19 test. There are two exceptions to this rule. The first exception is if a person’s race/ethnicity value is reported as “Unknown” on their first test and then on a subsequent test they report “Asian;” "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" or "White”, then this subsequent reported race/ethnicity will overwrite the previous recording of “Unknown”. If a person has only ever selected “Unknown” as their race/ethnicity, then it will be recorded as “Unknown.” This change provides more specific and actionable data on who is tested in San Francisco.
The second exception is if a person ever marks “Hispanic or Latino/a, all races” for race/ethnicity then this choice will always overwrite any previous or future response. This is because it is an overarching category that can include any and all other races and is mutually exclusive with the other responses.
A person's race/ethnicity will be recorded as “Multi-racial” if they select two or more values among the following choices: “Asian,” “Black or African American,” “American Indian or Alaska Native,” “Native Hawaiian or Other Pacific Islander,” “White,” or “Other.” If a person selects a combination of two or more race/ethnicity answers that includes “Hispanic or Latino/a, all races” then they will still be recorded as “Hispanic or Latino/a, all races”—not as “Multi-racial.”
C. HOW THE DATASET IS CREATED COVID-19 laboratory test data is based on electronic laboratory test reports. Deduplication, quality assurance measures and other data verification processes maximize accuracy of laboratory test information.
D. UPDATE PROCESS Updates automatically at 5:00AM Pacific Time each day. Redundant runs are scheduled at 7:00AM and 9:00AM in case of pipeline failure.
E. HOW TO USE THIS DATASET San Francisco population estimates for race/ethnicity can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).
Due to the high degree of variation in the time needed to complete tests by different labs there is a delay in this reporting. On March 24, 2020 the Health Officer ordered all labs in the City to report complete COVID-19 testing information to the local and state health departments.
In order to track trends over time, a user can analyze this data by sorting or filtering by the "specimen_collection_date" field.
Calculating Percent Positivity: The positivity rate is the percentage of tests that return a positive result for COVID-19 (positive tests divided by the sum of positive and negative tests). Indeterminate results, which could not conclusively determine whether COVID-19 virus was present, are not included in the calculation of percent positive. When there are fewer than 20 positives tests for a given race/ethnicity and time period, the positivity rate is not calculated for the public tracker because rates of small test counts are less reliable.
Calculating Testing Rates: To calculate the testing rate per 10,000 residents, divide the total number of tests collected (positive, negative, and indeterminate results) for the specified race/ethnicity by the total number of residents who identify as that race/ethnicity (according to the 2016-2020 American Community Survey (ACS) population estimate), then multiply by 10,000. When there are fewer than 20 total tests for a given race/ethnicity and time period, the testing rate is not calculated for the public tracker because rates of small test counts are less reliable.
Read more about how this data is updated and validated daily: https://sf.gov/information/covid-19-data-questions
F. CHANGE LOG
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TwitterTake-up rate within 2 years of tranistioning out of military by race/ethnicity and VA Benefit or Service.
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TwitterTake-up rate within 2 fiscal years after separation from military service by race/ethnicity and sex.
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TwitterCommunity Specific Profiles are grouped by race and ethnicity. We measure by race, ethnicity, and other demographics to understand the specific needs of different communities and evaluate effective service delivery and accountability. This dataset is the groupings used to combine projects with multiple levels and types of data standards. These include the minimum and comprehensive race and ethnicity categories from the City of Portland Rescue Plan Data Standards. They also include race and ethnicity categories in the HUD HMIS data standards.-- Additional Information: Category: ARPA Update Frequency: As Necessary-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=60968
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The dataset tabulates the population of Gold Hill by race. It includes the population of Gold Hill across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Gold Hill across relevant racial categories.
Key observations
The percent distribution of Gold Hill population by race (across all racial categories recognized by the U.S. Census Bureau): 87.03% are white, 0.55% are American Indian and Alaska Native, 1.03% are Asian, 2.06% are some other race and 9.34% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Gold Hill Population by Race & Ethnicity. You can refer the same here
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The dataset tabulates the population of Lehigh County by race. It includes the population of Lehigh County across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Lehigh County across relevant racial categories.
Key observations
The percent distribution of Lehigh County population by race (across all racial categories recognized by the U.S. Census Bureau): 66.77% are white, 6.94% are Black or African American, 0.33% are American Indian and Alaska Native, 3.51% are Asian, 0.04% are Native Hawaiian and other Pacific Islander, 9.63% are some other race and 12.78% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Lehigh County Population by Race & Ethnicity. You can refer the same here
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TwitterThis dataset contains statistically weighted estimates of the Race & Ethnicity of 47 key health workforce professions actively licensed in California as of December 3rd, 2024. These metrics can be compared by workforce category, license type, region, county and age.
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TwitterThis data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees by race and ethnicity overall and by three subpopulation topics: scope of Medicaid and CHIP benefits, age group, and eligibility category. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, and Puerto Rico who were enrolled for at least one day in the calendar year. Enrollees in Guam, American Samoa, the Northern Mariana Islands, and the U.S. Virgin Islands are not included. Results shown for the age group and eligibility category subpopulation topics only include enrollees with comprehensive Medicaid and CHIP benefits in the year. Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on information shown in the brief: "Race and ethnicity of the national Medicaid and CHIP population in 2020." Enrollees are assigned to six race and ethnicity categories using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG). Enrollees are assigned to a child (ages 0-18) or adult (ages 19 and older) subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to the comprehensive benefits or limited benefits subpopulation according to the criteria in the "Identifying Beneficiaries with Full-Scope, Comprehensive, and Limited Benefits in the TAF" DQ Atlas brief. Enrollees are assigned to an eligibility category subpopulation using their latest reported eligibility group code, CHIP code, and age in the calendar year. Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.
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TwitterThis report summarizes data on COVID-19 cases and COVID-19 associated deaths by race/ethnicity for the state of Connecticut and the 10 largest Connecticut towns. Data on race/ethnicity are missing on almost half (47%) of reported COVID-19 cases. CT DPH has urged healthcare providers and laboratories to complete information on race/ethnicity for all COVID-19 cases. All data in this report are preliminary; data will be updated as new COVID-19 case reports are received and data errors are corrected. Data on COVID-19 cases and COVID-19-associated deaths were last updated on April 20, 2020 at 3 PM. Information about race and ethnicity are collected on the Connecticut Department of Public Health (DPH) COVID-19 case report form, which is completed by healthcare providers for laboratory-confirmed COVID-19 cases. Information about the race/ethnicity of COVID-19-associated deaths also are collected by the Connecticut Office of the Chief Medical Examiner and shared with DPH. Race/ethnicity categories used in this report are mutually exclusive. People answering ‘yes’ to more than one race category are counted as ‘other’.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the population of Palisade by race. It includes the population of Palisade across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Palisade across relevant racial categories.
Key observations
The percent distribution of Palisade population by race (across all racial categories recognized by the U.S. Census Bureau): 85.39% are white, 0.39% are some other race and 14.22% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Palisade Population by Race & Ethnicity. You can refer the same here
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The dataset tabulates the population of Junction City by race. It includes the population of Junction City across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Junction City across relevant racial categories.
Key observations
The percent distribution of Junction City population by race (across all racial categories recognized by the U.S. Census Bureau): 88.75% are white, 0.03% are Black or African American, 1.10% are American Indian and Alaska Native, 1.69% are some other race and 8.43% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Junction City Population by Race & Ethnicity. You can refer the same here
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The dataset tabulates the population of Cross town by race. It includes the population of Cross town across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Cross town across relevant racial categories.
Key observations
The percent distribution of Cross town population by race (across all racial categories recognized by the U.S. Census Bureau): 92.73% are white, 1.36% are some other race and 5.91% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Cross town Population by Race & Ethnicity. You can refer the same here
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The dataset tabulates the population of Mount Vernon by race. It includes the population of Mount Vernon across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Mount Vernon across relevant racial categories.
Key observations
The percent distribution of Mount Vernon population by race (across all racial categories recognized by the U.S. Census Bureau): 92.02% are white, 0.92% are Black or African American, 0.11% are American Indian and Alaska Native, 0.25% are Asian, 3.50% are some other race and 3.20% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Mount Vernon Population by Race & Ethnicity. You can refer the same here
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The dataset tabulates the population of Lake City by race. It includes the population of Lake City across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Lake City across relevant racial categories.
Key observations
The percent distribution of Lake City population by race (across all racial categories recognized by the U.S. Census Bureau): 58.50% are white, 31.76% are Black or African American, 0.06% are American Indian and Alaska Native, 1.23% are Asian, 2.81% are some other race and 5.64% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Lake City Population by Race & Ethnicity. You can refer the same here
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Context
The dataset tabulates the population of Nash by race. It includes the population of Nash across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Nash across relevant racial categories.
Key observations
The percent distribution of Nash population by race (across all racial categories recognized by the U.S. Census Bureau): 35.78% are white, 46.91% are Black or African American, 0.33% are American Indian and Alaska Native, 0.05% are Asian, 9.77% are some other race and 7.16% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Nash Population by Race & Ethnicity. You can refer the same here
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The dataset tabulates the population of Oak Leaf by race. It includes the population of Oak Leaf across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Oak Leaf across relevant racial categories.
Key observations
The percent distribution of Oak Leaf population by race (across all racial categories recognized by the U.S. Census Bureau): 72.43% are white, 12.50% are Black or African American, 0.23% are American Indian and Alaska Native, 4.22% are Asian, 1.08% are some other race and 9.53% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Oak Leaf Population by Race & Ethnicity. You can refer the same here
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The dataset tabulates the population of Athens by race. It includes the population of Athens across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Athens across relevant racial categories.
Key observations
The percent distribution of Athens population by race (across all racial categories recognized by the U.S. Census Bureau): 84.70% are white, 6.09% are Black or African American, 0.06% are American Indian and Alaska Native, 1.16% are Asian, 1.47% are some other race and 6.51% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Athens Population by Race & Ethnicity. You can refer the same here
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Context
The dataset tabulates the population of Federal Way by race. It includes the population of Federal Way across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Federal Way across relevant racial categories.
Key observations
The percent distribution of Federal Way population by race (across all racial categories recognized by the U.S. Census Bureau): 38.79% are white, 17.80% are Black or African American, 0.88% are American Indian and Alaska Native, 14.51% are Asian, 3.22% are Native Hawaiian and other Pacific Islander, 10.17% are some other race and 14.63% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Federal Way Population by Race & Ethnicity. You can refer the same here