Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Detroit 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 Detroit 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 Detroit town was 918, a 1.77% increase year-by-year from 2022. Previously, in 2022, Detroit town population was 902, an increase of 1.12% compared to a population of 892 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Detroit town increased by 100. In this period, the peak population was 918 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).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
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 Detroit town Population by Year. You can refer the same here
Detroit-specific ZIP code populations, along with their cumulative COVID case counts, deaths, and rates. Data provided by Detroit Health Department. The public-facing COVID Cases Dashboard is hosted at: detroitmi.gov/healthUPDATE* July 29 2021:The underlying calculation for disease date was updated to allow for individuals to appear on the curve in multiple locations if they experienced more than one case of COVID-19 that was at least 90 days apart.Geospatial information analysis was also improved and additional criterial for address clean up were implemented, which leads to more accurate case counts within Zip Codes. Some unverified addresses that may have appeared in previous Zip Code counts are now excluded.This change discourages direct comparison of dashboard visualizations and counts prior to the new calculation, and non-significant shifts in numbers will be noticed.Case numbers represent Detroit residents only. Some ZIP codes with very low case counts are excluded to protect privacy. Case counts are totals per ZIP code and are not adjusted for population. ZIP code totals are preliminary; addresses are updated as new information becomes available and counts are subject to change. Not all cases have an accurate location; only cases with a known ZIP code are represented. Where a ZIP code is split between cities, only the Detroit portion is shown (48203, 48211, 48212, 48236, 48239). The counts exclude cases among prisoners at the Wayne County Jail and known hospital or laboratory locations.ZIP_Code: The USPS ZIP postal code Clipped_ZIP_Population: The 2010 population of the ZIP code, clipped to include Detroit City residents only.ZIP_Case_Count: The current cumulative count of Confirmed COVID cases within the ZIP code, since the beginning of the pandemic. (Have a "Confimed" case status in MDSS)ZIP_Death_Count: The current cumulative count of Confirmed COVID cases within the ZIP code, since the beginning of the pandemic. (Have a "Confimed" case status in MDSS and are deceased)ZIP_Case_Rate: Rate of confirmed cases per 100 thousand residents in the ZIP code. For each zip, the rate was calculated by (C/P)*100000 C = the count of confirmed (MDSS case status = Confirmed) cases with a resident address in the ZIP code P = the population count of the ZIP codeZIP_Death_Rate: Rate of confirmed cases that were marked deceased, per 100 thousand residents in the ZIP code. For each zip, the rate was calculated by (D/P)*100000 D = the count of confirmed (MDSS case status = Confirmed) cases marked as deceased, with a resident address in the ZIP P = the population count of the ZIP code
The Group Quarters Facilities data layer contains information on both institutional and non-institutional group quarters facilities in Southeast Michigan. According to the Census Bureau, group quarters are places where people live or stay, in a group living arrangement, that is owned or managed by an entity providing housing and/or services for the residents. This is not a typical household-type living arrangement and the people living in group quarters are usually not related to one another. It is important to monitor the group quarters population because they are sampled as individuals within Census Bureau surveys, rather than as members of a household unit, and less information is reported.Group Quarters TypesInstitutional group quarters provide supervised custody or care to inmates or residents. This includes correctional facilities, assisted living, nursing homes, and memory care.Non-institutional group quarters house residents who are able or eligible to be in the labor force. This includes student and military housing, group homes, residential treatment centers, and religious housing.Group Quarters Facility CountsData on group quarters facilities is decentralized, and collected from a variety of federal and state agencies, educational institutions, industry associations, and private sources. Group Quarters Facility AttributesSEMCOG maintains a limited number of attributes on the group quarters facility points data layer. Please note that because a single building may contain group quarters of different types, there will be cases where there is multiple records for a single structure. Table GQ.1 list the current attributes of the buildings dataset: Table GQ.1Group Quarters Dataset AttributesFIELDTYPEDESCRIPTIONCOUNTY_IDIntegerFIPS county code.CITY_IDIntegerSEMCOG code identifying the municipality, or for Detroit, master plan neighborhood, in which the building is located.BUILDING_IDLong IntegerUnique identifier number of each building from SEMCOG’s buildings layer.IDENTIFIERVarchar(20)Unique identifier assigned by a government agency in their own systems.Most often this field is NULL.FAC_NAMEVarchar(50)Name of the group quarters facility record.FAC_ADDRESSVarchar(50)Mailing address of the group quarters facility record.FAC_CITYVarchar(50)Name of legal jurisdiction in which the facility is located.FAC_ZIPCODELong IntegerFive digit zip code of the mailing address of the group quarters facility.LICENSED_BEDSIntegerCount of licensed beds OR maximum capacity of the group quarters facility.RESIDENT_COUNTIntegerCount of residents in the facility in spring 2020.GQ_CODEIntegerGroup quarters facility type classification code.Please see below.Group Quarters Classification CodeSEMCOG’s group quarters classification codes are adopted from the coding system established by the U.S. Census Bureau to classify group quarters in their data products. There are several Census codes not used by SEMCOG as our region does not contain those types of facilities, and one additional code added for a different type of facility. More information on Census group quarters codes, including full descriptions of each classification, can be found on the Census Bureau’s web site. SEMCOG classifies student housing differently than the Census, separating dorms from fraternities and sororities regardless of whether they are located on campus. In addition, student cooperative housing is added as an additional type due to the large number of such buildings in Ann Arbor. In addition, Census counts of homeless persons are distributed to government buildings in the largest community in each county and the City of Detroit to ensure their inclusion in the data layer.Table GQ.2Group Quarters Classification CodesGQ CODEDESCRIPTIONPRIMARY SOURCE102Federal PrisonsU.S. Bureau of Prisons103State PrisonsMichigan Department of Corrections104County JailsMichigan Department of Corrections201Juvenile Group HomesMichigan Department of Licensing and Regulatory Affairs202Juvenile Residential Treatment CentersU.S. Substance Abuse and Mental Health Services Admin203Juvenile Correctional FacilitiesMichigan Department of Corrections301Assisted Living and Skilled Nursing HomesU.S. Centers for Medicare and Medicaid andMichigan Department of Licensing and Regulatory Affairs401Adult Mental Hospitals and Psychiatric Units in HospitalsMichigan Department of Licensing and Regulatory Affairs402Pediatric Mental Hospitals and Psychiatric Units in HospitalsMichigan Department of Licensing and Regulatory Affairs403Palliative Care such as Hospice, Traumatic Brain Injury, etc.Michigan Department of Licensing and Regulatory Affairs404Special Psychiatric PopulationsMichigan Department of Licensing and Regulatory Affairs405Neonatal Intensive Care UnitsMichigan Department of Licensing and Regulatory Affairs501College Student DormitoriesIndividual College Housing Department502Fraternities and SororitiesPublic Research503College Student Cooperative HousingPublic Research701Transitional Housing SheltersPublic Research and U.S. Census Bureau702Homeless SheltersPublic Research and U.S. Census Bureau801Adult Foster HomesMichigan Department of Licensing and Regulatory Affairs802Adult Residential Treatment CentersU.S. Substance Abuse and Mental Health Services Admin904Religious Quarters and Domestic Violence SheltersMichigan Department of Licensing and Regulatory Affairs
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Detroit by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Detroit across both sexes and to determine which sex constitutes the majority.
Key observations
There is a slight majority of female population, with 52.48% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.
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 Detroit Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Detroit by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Detroit. The dataset can be utilized to understand the population distribution of Detroit by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Detroit. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Detroit.
Key observations
Largest age group (population): Male # 25-29 years (24,143) | Female # 30-34 years (26,970). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
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 Detroit Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Detroit. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Detroit population by race & ethnicity, the population is predominantly Black or African American. This particular racial category constitutes the majority, accounting for 77.94% of the total residents in Detroit. Notably, the median household income for Black or African American households is $34,844. Interestingly, despite the Black or African American population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $58,953. This reveals that, while Black or African Americans may be the most numerous in Detroit, Asian households experience greater economic prosperity in terms of median household income.
https://i.neilsberg.com/ch/detroit-mi-median-household-income-by-race.jpeg" alt="Detroit median household income diversity across racial categories">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-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 Detroit median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Detroit town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Detroit town. The dataset can be utilized to understand the population distribution of Detroit town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Detroit town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Detroit town.
Key observations
Largest age group (population): Male # 40-44 years (52) | Female # 50-54 years (77). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
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 Detroit town Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Detroit township by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Detroit township. The dataset can be utilized to understand the population distribution of Detroit township by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Detroit township. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Detroit township.
Key observations
Largest age group (population): Male # 70-74 years (122) | Female # 60-64 years (100). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
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 Detroit township Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Detroit. The dataset can be utilized to gain insights into gender-based income distribution within the Detroit population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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 Detroit median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Detroit Lakes. The dataset can be utilized to gain insights into gender-based income distribution within the Detroit Lakes population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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 Detroit Lakes median household income by race. You can refer the same here
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Detroit 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 Detroit 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 Detroit town was 918, a 1.77% increase year-by-year from 2022. Previously, in 2022, Detroit town population was 902, an increase of 1.12% compared to a population of 892 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Detroit town increased by 100. In this period, the peak population was 918 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).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
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 Detroit town Population by Year. You can refer the same here