About this dataset

Context

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

Key observations

The percent distribution of Melbourne population by race (across all racial categories recognized by the U.S. Census Bureau): 96.99% are white, 0.45% are Black or African American, 0.40% are Asian, 0.40% are some other race and 1.75% are multiracial.

Content

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:

• 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 Melbourne
• Population: The population of the racial category (excluding ethnicity) in the Melbourne is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Melbourne 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 Melbourne Population by Race & Ethnicity. You can refer the same here

University Student Enrollment Data

Demographics and Academic Details of University Student Enrollments

By Gove [source]

About this dataset

This dataset represents a comprehensive collection of valuable and relevant information regarding student registration across a multitude of universities. It provides an in-depth insight into various aspects of this subject matter, making it an indispensable tool for any research related to university student registrations.

The information contained within this particular dataset offers extensive details about each individual student. This rich, individual data includes demographic particulars such as their age, gender and nationality - details which could yield interesting points of analysis when correlated against other factors within the data.

Additionally, this dataset maintains academic records for each registered student, providing detailed descriptions like course of study and year of enrollment. This formative data aids in understanding students' registration patterns over the years or tracking their academic progression throughout their tenure at university.

Moreover, the dataset is also expected to contain vital statistics tied to individual universities where these students are enrolled. Such expected details include each institution's location which can provide geo-political or socio-economic insights pertaining to university selection trends amongst students.

Further enriching the body of knowledge available within this repository is potential data related to specific course offerings by these universities – a feature useful for assessing popular disciplines or identifying shifts in educational trends based on subject popularity.

Another significant set of information which might be found inside this repository pertains to faculty specifics including number and qualifications alongside overall ranking standings – these can serve as additional metrics in gauging perceived quality or reputation among the registered student bodies with respect to selecting universities for further studies.

In sum, whether you’re interested in mapping out educational trends over time; analyzing demographic profiles against choice courses; studying correlations between nationality and select colleges; or looking into institutional rankings’ sway over enrollments – this amalgamation holds invaluable keys that unlock numerous possibilities through exploration via different combinations making it versatile enough for diverse investigatory needs while offering deep analytical potentials for those willing explore its depths

How to use the dataset

• Student Demographic Analysis: You can use this dataset to understand the demographic distribution of students across universities. This involves analyzing information related to age, nationality, and gender among others. For example, you might want to find out which university has the highest number of international students or what is the gender ratio in a specific course of study.

• Analysis on Courses & Faculties: Data from this dataset can be used for insightful exploration into various courses and faculties offered by different universities. You may want to investigate questions like What is the most popular course?or Which university has a larger faculty for science stream?.

• University Comparison: The data allows for comparison between different universities based on their student population, diversity, departments/faculties and courses being offered etc.. In doing so, you could discern trends or patterns linked with university ranking and location that may play role in student enrollment decisions.

• Tracking Enrollment Trends: By examining factors such as year of enrollment and course selections over time, it becomes possible to track trends within each school's student body population or wider academic field at large scale over multiple years; potentially even predicting future movements.

• The dataset also provides excellent resources for machine learning applications such as predictive models for student academic performance or building recommender systems capable off suggesting best suited unversities or courses based on individual characterstics.

• This data set can also aid administrative decision making processes around things like budget allocation (based on number of students per faculty), policy changes related with improving diversity within campus etc., providing valuable quantitative backing towards making such important decisions.

Remember that while using this dataset correctly respecting privacy norms is paramount given sensitive nature involved with personal details included here; always adhere...

U.S. Mortality and Health Indicators

Impact of Risk Factors on Population Health Outcomes

By Data Society [source]

About this dataset

This dataset provides county-level mortality and health indicators that are useful for measuring the impact of health policies in the United States. It includes data elements and values from over a dozen categories, including Demographics, Leading Causes of Death, Summary Measures of Health, Measures of Birth and Death, Relative Health Importance, Vulnerable Populations and Environmental Health, Preventive Services Use, Risk Factors and Access to Care. Additionally, this dataset offers Healthy People 2010 Targets and US Percentages or Rates for easy comparison across states. With comprehensive information for each county in each indicator domain available here at your fingertips could help you get insight into American population health from the local level like never before. Discover trends on disease outbreaks or immunizations that are unprecedentedly localized with insights from this dataset!

More Datasets

For more datasets, click here.

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How to use the dataset

This dataset contains various data elements related to the mortality and health of the US population at various levels such as county, state, etc. This dataset is an ideal source of information for researchers and policy makers who are interested in exploring patterns in the mortality and health of US citizens.

In order to use this dataset effectively, it is important to understand the different indicators included as well as how to interpret these indicators. In this guide we will look at each indicator domain separately so that users can easily identify which relevant data elements they need for their analysis.

Demographics: The Demographics indicator domain includes data elements related to demographic characteristics such as age composition, gender composition etc. These indicators can be used to explore trends across different parts of the country or identify disparities among populations.

Leading Causes of Death: The Leading Causes of Death indicator domain contains information on fatalities by cause over a set period of time -- either two years or five years depending on availability -- so that researchers can identify causes that pose major threats to public health overall or in more specific regions such as certain counties. It is important to note that these largely report figures based on death certificates which may not always tell an exact story due to reporting inaccuracies caused by both individual factors and registration biases across counties/states over time.

 **Summary Measures Of Health**: The Summary Measures Of Health Indicator Domain includes measures commonly used for gauging overall population health such as birth rates and death rates but also key quality-of-life considerations like prevalence rate physical activity rate . These can be used together with other data sources (such as income info) when analyzing population health outcomes from a broader perspective than individual diseases or conditions would allow for . 

 **Measures Of Birth And Death**: This category provides further insight into the important summary level figures mentioned earlier by providing observations about frequency , timing , type etc where available . Additionally , it offers valuable insights about trends related specifically (among others ) out - migration /in - migration mortality ratio changes/births outside hospitals marriage age / labor force participation trends etc – all essential ingredients when trying solve complex issues related improving public one's life expectancy positively  

 **Relative Health Importance & Vulnerable Populations And Environment Capacity :** This section covers two closely intertwined fields revealing how they interact – socioeconomic status disparities & environment quality – around boundaries & neighborhoods influencing risks factors (not only related medical matters ) aspects such disabilities insurance coverage alcohol use & smoking habits road fatalities veh

Research Ideas

• Using the Health Status Indicators as input features, machine learning models can be built to predict county-level mortality rate, which can then be used as an important indicator for health and medical resource allocation.
• The data can also be used to analyze the social determinants of health in different counties by combining with socioeconomic indicators such as poverty, population density and educational attainment levels.
• Additionally, the dataset could help assess th...

Description:

The "Daily Social Media Active Users" dataset provides a comprehensive and dynamic look into the digital presence and activity of global users across major social media platforms. The data was generated to simulate real-world usage patterns for 13 popular platforms, including Facebook, YouTube, WhatsApp, Instagram, WeChat, TikTok, Telegram, Snapchat, X (formerly Twitter), Pinterest, Reddit, Threads, LinkedIn, and Quora. This dataset contains 10,000 rows and includes several key fields that offer insights into user demographics, engagement, and usage habits.

Dataset Breakdown:

• Platform: The name of the social media platform where the user activity is tracked. It includes globally recognized platforms, such as Facebook, YouTube, and TikTok, that are known for their large, active user bases.

• Owner: The company or entity that owns and operates the platform. Examples include Meta for Facebook, Instagram, and WhatsApp, Google for YouTube, and ByteDance for TikTok.

• Primary Usage: This category identifies the primary function of each platform. Social media platforms differ in their primary usage, whether it's for social networking, messaging, multimedia sharing, professional networking, or more.

• Country: The geographical region where the user is located. The dataset simulates global coverage, showcasing users from diverse locations and regions. It helps in understanding how user behavior varies across different countries.

• Daily Time Spent (min): This field tracks how much time a user spends on a given platform on a daily basis, expressed in minutes. Time spent data is critical for understanding user engagement levels and the popularity of specific platforms.

• Verified Account: Indicates whether the user has a verified account. This feature mimics real-world patterns where verified users (often public figures, businesses, or influencers) have enhanced status on social media platforms.

• Date Joined: The date when the user registered or started using the platform. This data simulates user account history and can provide insights into user retention trends or platform growth over time.

Context and Use Cases:

• This synthetic dataset is designed to offer a privacy-friendly alternative for analytics, research, and machine learning purposes. Given the complexities and privacy concerns around using real user data, especially in the context of social media, this dataset offers a clean and secure way to develop, test, and fine-tune applications, models, and algorithms without the risks of handling sensitive or personal information.

Researchers, data scientists, and developers can use this dataset to:

• Model User Behavior: By analyzing patterns in daily time spent, verified status, and country of origin, users can model and predict social media engagement behavior.

• Test Analytics Tools: Social media monitoring and analytics platforms can use this dataset to simulate user activity and optimize their tools for engagement tracking, reporting, and visualization.

• Train Machine Learning Algorithms: The dataset can be used to train models for various tasks like user segmentation, recommendation systems, or churn prediction based on engagement metrics.

• Create Dashboards: This dataset can serve as the foundation for creating user-friendly dashboards that visualize user trends, platform comparisons, and engagement patterns across the globe.

• Conduct Market Research: Business intelligence teams can use the data to understand how various demographics use social media, offering valuable insights into the most engaged regions, platform preferences, and usage behaviors.

• Sources of Inspiration: This dataset is inspired by public data from industry reports, such as those from Statista, DataReportal, and other market research platforms. These sources provide insights into the global user base and usage statistics of popular social media platforms. The synthetic nature of this dataset allows for the use of realistic engagement metrics without violating any privacy concerns, making it an ideal tool for educational, analytical, and research purposes.

The structure and design of the dataset are based on real-world usage patterns and aim to represent a variety of users from different backgrounds, countries, and activity levels. This diversity makes it an ideal candidate for testing data-driven solutions and exploring social media trends.

Future Considerations:

As the social media landscape continues to evolve, this dataset can be updated or extended to include new platforms, engagement metrics, or user behaviors. Future iterations may incorporate features like post frequency, follower counts, engagement rates (likes, comments, shares), or even sentiment analysis from user-generated content.

By leveraging this dataset, analysts and data scientists can create better, more effective strategies ...

About this dataset

Context

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

Key observations

The percent distribution of Highland County population by race (across all racial categories recognized by the U.S. Census Bureau): 95.29% are white, 1.48% are Black or African American, 0.18% are American Indian and Alaska Native, 0.11% are Asian, 0.27% are some other race and 2.68% are multiracial.

https://i.neilsberg.com/ch/highland-county-oh-population-by-race.jpeg" alt="Highland County population by race">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Highland County
• Population: The population of the racial category (excluding ethnicity) in the Highland County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Highland County 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 Highland County Population by Race & Ethnicity. You can refer the same here

Coronavirus (covid-19) in Sierra Leone

This repository contains datasets relating to coronavirus in Sierra Leone, as well as on demographic and other information from the 2015 Population and Household Census (PHC). It also includes mapping shapefiles by district, so that you can map the district-level coronavirus statistics.

See here for a full description of how the data files have been created from the source data, including the R code.

Last updated: 10 June 2020.

Context

The novel 2019 coronavirus (covid-19) arrived late to West Africa and Sierra Leone in particular. This dataset provides the number of reported cases on a district-by-district basis for Sierra Leone, as well as various additional statistics at the country level. In addition, I provide district-by-district data on demographics and households' main sources of information, both from the 2015 census. For convenience, I also provide shapefiles for mapping the 14 districts of Sierra Leone.

Content

The dataset consists of four main files, which are in the output folder. See the column descriptions below for further details.

1. Coronavirus confirmed cases by district (sl_districts_coronavirus.csv). I found the original data by looking in the static/js/data folder in the source code for covid19.mic.gov.sl, last accessed 10 June 2020. The file contains the cumulative number of confirmed coronavirus cases in the 14 districts of Sierra Leone as a time series. I have used the R tidyverse to reshape the data and ensure naming is consistent with the other data files.

2. Demographic statistics by district (sl_districts_demographics.csv). Data from the 2015 Population and Housing Census (PHC), sourced from Open Data Sierra Leone. The dataset covers the 14 districts of Sierra Leone, which increased to 16 in 2017. Last accessed 10 June 2020.

3. Main Sources of Information by district (sl_districts_info_sources.csv). Data from the 2015 Population and Housing Census (PHC), sourced from Open Data Sierra Leone. The dataset presents the main sources of information, such as television or radio, for households in the 14 districts of Sierra Leone. Last accessed 2 June 2020. I note that I have made one correction to the source data (see R code with correction here).

4. Country-wide coronavirus statistics for Sierra Leone (sl_national_coronavirus.csv). The original data also comes from covid19.mic.gov.sl, last accessed 10 June 2020. The file contains numerous statistics as time series, listed in the Column Description section below. I note that there are various potential issues in the file which I leave the user to decide how to deal with (duplicate datetimes, inconsistent statistics).

Additionally I include a set of five files with district-by-district mapping (shapefiles) and other data, unchanged from their original source. Each file is labelled in the following way: sl_districts_mapping.*. These files come from Direct Relief Open Data on ArcGIS Hub. The data also include district-level data on maternal child health attributes, which was the original context of the mapping data.

Column Descriptions

Coronavirus confirmed cases by district sl_districts_coronavirus.csv:

1. date: Date of reporting
2. district: District of Sierra Leone (based on pre-2017 administrative boundaries)
3. confirmed_cases: Cumulative number of confirmed coronavirus cases; NA if no data reported
4. decrease: Dummy variable indicating whether the number of reported cases has been revised down. NA if no reported cases on that date; 1 if there is a decrease from the last reported cases; 0 otherwise

Demographic statistics by district sl_districts_demographics.csv:

1. district: District of Sierra Leone (based on pre-2017 administrative boundaries)
2. d_code: District code
3. d_id: District id
4. total_pop: Total population in district
5. pop_share: District's share of total country population
6. t_male: Total male population
7. t_female: Total female population
8. s_ratio: (*) Sex ratio at birth (number of males for every 100 females, under the age of 1)
9. t_urban: Total urban population
10. t_rural: Total rural population
11. prop_urban: Proportion urban
12. t_h_pop: Sum of h_male and h_female
13. h_male: (?)
14. h_female: (?)
15. t_i_pop: Sum of i_male and i_female
16. i_male: (?)
17. i_female: (?)
18. working_pop: Working population
19. depend_pop: Dependent population

...

About this dataset

Context

The dataset tabulates the Major County population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Major County. The dataset can be utilized to understand the population distribution of Major County by age. For example, using this dataset, we can identify the largest age group in Major County.

Key observations

The largest age group in Major County, OK was for the group of age 5-9 years with a population of 605 (7.80%), according to the 2021 American Community Survey. At the same time, the smallest age group in Major County, OK was the 75-79 years with a population of 236 (3.04%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Major County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Major County 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 Major County Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Main township population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Main township. The dataset can be utilized to understand the population distribution of Main township by age. For example, using this dataset, we can identify the largest age group in Main township.

Key observations

The largest age group in Main Township, Pennsylvania was for the group of age 10 to 14 years years with a population of 167 (11.16%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Main Township, Pennsylvania was the 80 to 84 years years with a population of 14 (0.94%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Main township is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Main township 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 Main township Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Florida City population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Florida City. The dataset can be utilized to understand the population distribution of Florida City by age. For example, using this dataset, we can identify the largest age group in Florida City.

Key observations

The largest age group in Florida City, FL was for the group of age 5-9 years with a population of 1,729 (13.46%), according to the 2021 American Community Survey. At the same time, the smallest age group in Florida City, FL was the 85+ years with a population of 95 (0.74%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Florida City is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Florida 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 Florida City Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Prior Lake population by race (across all racial categories recognized by the U.S. Census Bureau): 88.65% are white, 1.04% are Black or African American, 0.73% are American Indian and Alaska Native, 3.88% are Asian, 0.01% are Native Hawaiian and other Pacific Islander, 1.75% are some other race and 3.95% are multiracial.

https://i.neilsberg.com/ch/prior-lake-mn-population-by-race.jpeg" alt="Prior Lake population by race">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Prior Lake
• Population: The population of the racial category (excluding ethnicity) in the Prior Lake is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Prior Lake 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 Prior Lake Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Delmar population by race (across all racial categories recognized by the U.S. Census Bureau): 61.36% are white, 26.03% are Black or African American, 0.38% are American Indian and Alaska Native, 2.68% are Asian, 1.76% are some other race and 7.80% are multiracial.

Content

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:

• 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 Delmar
• Population: The population of the racial category (excluding ethnicity) in the Delmar is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Delmar 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 Delmar Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Main township by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Main township. The dataset can be utilized to understand the population distribution of Main township by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Main 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 Main township.

Key observations

Largest age group (population): Male # 10-14 years (92) | Female # 15-19 years (122). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

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

• Age Group: This column displays the age group for the Main township population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Main township is shown in the following column.
• Population (Female): The female population in the Main township is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Main township for each age group.

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 Main township Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Port Angeles population by race (across all racial categories recognized by the U.S. Census Bureau): 83.75% are white, 0.98% are Black or African American, 1.97% are American Indian and Alaska Native, 0.92% are Asian, 2.56% are some other race and 9.83% are multiracial.

Content

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:

• 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 Port Angeles
• Population: The population of the racial category (excluding ethnicity) in the Port Angeles is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Port Angeles 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 Port Angeles Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Port Deposit population by race (across all racial categories recognized by the U.S. Census Bureau): 71.97% are white, 17.42% are Black or African American, 2.08% are Asian, 0.76% are some other race and 7.77% are multiracial.

Content

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:

• 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 Port Deposit
• Population: The population of the racial category (excluding ethnicity) in the Port Deposit is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Port Deposit 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 Port Deposit Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Mammoth Lakes population by race (across all racial categories recognized by the U.S. Census Bureau): 73.93% are white, 0.62% are American Indian and Alaska Native, 3.10% are Asian, 5.90% are some other race and 16.45% are multiracial.

Content

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:

• 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 Mammoth Lakes
• Population: The population of the racial category (excluding ethnicity) in the Mammoth Lakes is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Mammoth Lakes 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 Mammoth Lakes Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Bethany population by race (across all racial categories recognized by the U.S. Census Bureau): 65.94% are white, 10.99% are Black or African American, 3.21% are American Indian and Alaska Native, 0.66% are Asian, 0.02% are Native Hawaiian and other Pacific Islander, 5.07% are some other race and 14.10% are multiracial.

Content

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:

• 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 Bethany
• Population: The population of the racial category (excluding ethnicity) in the Bethany is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Bethany 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 Bethany Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Newton population by race (across all racial categories recognized by the U.S. Census Bureau): 71.07% are white, 2.24% are Black or African American, 0.37% are American Indian and Alaska Native, 16.60% are Asian, 0.02% are Native Hawaiian and other Pacific Islander, 2.41% are some other race and 7.29% are multiracial.

Content

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:

• 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 Newton
• Population: The population of the racial category (excluding ethnicity) in the Newton is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Newton 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 Newton Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Economy population by race (across all racial categories recognized by the U.S. Census Bureau): 94.13% are white, 1.24% are Black or African American, 0.14% are American Indian and Alaska Native, 0.07% are Asian, 0.09% are some other race and 4.34% are multiracial.

Content

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:

• 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 Economy
• Population: The population of the racial category (excluding ethnicity) in the Economy is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Economy 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 Economy Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Daisy population by race (across all racial categories recognized by the U.S. Census Bureau): 84.68% are white, 8.06% are Asian and 7.26% are multiracial.

Content

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:

• 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 Daisy
• Population: The population of the racial category (excluding ethnicity) in the Daisy is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Daisy 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 Daisy Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Airport Drive population by race (across all racial categories recognized by the U.S. Census Bureau): 92.61% are white, 0.89% are Black or African American, 0.25% are American Indian and Alaska Native, 0.38% are Asian, 0.89% are some other race and 4.97% are multiracial.

Content

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:

• 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 Airport Drive
• Population: The population of the racial category (excluding ethnicity) in the Airport Drive is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Airport Drive 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 Airport Drive Population by Race & Ethnicity. You can refer the same here