100+ datasets found
  1. U.S. adults' beliefs on increasing diversity at work 2023, by race

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). U.S. adults' beliefs on increasing diversity at work 2023, by race [Dataset]. https://www.statista.com/statistics/1391380/us-adults-beliefs-on-increasing-diversity-at-work-by-race/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 6, 2023 - Feb 12, 2023
    Area covered
    United States
    Description

    According to a survey conducted in 2023, ** percent of employed adults who were Black believed that focusing on increasing diversity, equity, and inclusion at work was a good thing in the United States, while ** percent of employed adults who were White shared this belief.

  2. a

    Racial Diversity Index - City

    • vital-signs-bniajfi.hub.arcgis.com
    • hub.arcgis.com
    Updated Feb 27, 2020
    + more versions
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    Baltimore Neighborhood Indicators Alliance (2020). Racial Diversity Index - City [Dataset]. https://vital-signs-bniajfi.hub.arcgis.com/datasets/racial-diversity-index-city
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    Dataset updated
    Feb 27, 2020
    Dataset authored and provided by
    Baltimore Neighborhood Indicators Alliance
    Area covered
    Description

    The percent chance that two people picked at random within an area will be of a different race/ethnicity. This number does not reflect which race/ethnicity is predominant within an area. The higher the value, the more racially and ethnically diverse an area. Source: U.S. Bureau of the Census, American Community Survey Years Available: 2010, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2017-2021, 2018-2022, 2019-2023

  3. Racial diversity in the workforce of Bank of America in the U. S. 2019-2024

    • statista.com
    Updated Mar 13, 2025
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    Statista (2025). Racial diversity in the workforce of Bank of America in the U. S. 2019-2024 [Dataset]. https://www.statista.com/statistics/1319055/us-racial-diversity-bank-of-america/
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    Dataset updated
    Mar 13, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Bank of America's workforce has undergone a significant shift in racial diversity over the past six years. The share of white employees decreased from 53.2 percent in 2019 to 47.2 percent in 2024, marking a notable change in the company's demographic composition. Meanwhile, the representation of Hispanic, Asian, and Black racial groups grew steadily. The second-largest racial group in the observed period was Hispanic, whose share increased from 17.9 to 19.2 percent.

  4. A

    Diversity Index

    • data.amerigeoss.org
    • data.wu.ac.at
    csv, geojson, json +1
    Updated Jul 26, 2019
    + more versions
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    United States (2019). Diversity Index [Dataset]. https://data.amerigeoss.org/ja/dataset/diversity-index
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    json, shp, geojson, csvAvailable download formats
    Dataset updated
    Jul 26, 2019
    Dataset provided by
    United States
    Description

    This map service summarizes racial and ethnic diversity in the United States in 2012.

    The Diversity Index shows the likelihood that two persons chosen at random from the same area, belong to different race or ethnic groups. The index ranges from 0 (no diversity) to 100 (complete diversity). Diversity in the U.S. population is increasing. The diversity score for the entire United States in 2012 is 61.

    The data shown is from Esri's 2012 Updated Demographics. The map adds increasing level of detail as you zoom in, from state, to county, to ZIP Code, to tract, to block group data. This map shows Esri's 2012 estimates using Census 2010 geographies.

  5. U.S. opinion on diversity and inclusion importance in work culture 2019, by...

    • statista.com
    Updated May 26, 2025
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    Statista (2025). U.S. opinion on diversity and inclusion importance in work culture 2019, by community [Dataset]. https://www.statista.com/statistics/1195846/us-worker-opinion-diversity-inclusion-workplace-importance-community/
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    Dataset updated
    May 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 10, 2019 - Jan 24, 2019
    Area covered
    United States
    Description

    In a January 2019 survey, 65 percent of participants who identified themselves as LGBTQ from the United States said that they believe diversity and inclusion is essential to creating a supportive workplace culture. This is compared to only 35 percent of white male participants who felt the same way. All survey participants were full-time working professionals.

  6. H

    Diversity Data: Metropolitan Quality of Life Data

    • data.niaid.nih.gov
    • dataverse.harvard.edu
    Updated Jan 11, 2011
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    (2011). Diversity Data: Metropolitan Quality of Life Data [Dataset]. http://doi.org/10.7910/DVN/FQINUJ
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    Dataset updated
    Jan 11, 2011
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Users can obtain descriptions, maps, profiles, and ranks of U.S. metropolitan areas pertaining to quality of life, diversity, and opportunities for racial and ethnic groups in the U.S. BackgroundThe Diversity Data project operates a website for users to explore how U.S. metropolitan areas perform on evidence-based social measures affecting quality of life, diversity and opportunity for racial and ethnic groups in the United States. These indicators capture a broad definition of quality of life and health, including opportunities for good schools, housing, jobs, wages, health and social services, and safe neighborhoods. This is a useful resource for people inter ested in advocating for policy and social change regarding neighborhood integration, residential mobility, anti-discrimination in housing, urban renewal, school quality and economic opportunities. The Diversity Data project is an ongoing project of the Harvard School of Public Health (Department of Society, Human Development and Health). User FunctionalityUsers can obtain a description, profile and rank of U.S. metropolitan areas and compare ranks across metropolitan areas. Users can also generate maps which demonstrate the distribution of these measures across the United States. Demographic information is available by race/ethnicity. Data NotesData are derived from multiple sources including: the U.S. Census Bureau; National Center for Health Statistics' Vital Statistics Natality Birth Data; Natio nal Center for Education Statistics; Union CPS Utilities Data CD; National Low Income Housing Coalition; Freddie Mac Conventional Mortgage Home Price Index; Neighborhood Change Database; Joint Center for Housing Studies of Harvard University; Federal Financial Institutions Examination Council Home Mortgage Disclosure Act (HMD); Dr. Russ Lopez, Boston University School of Public Health, Department of Environmental Health; HUD State of the Cities Data Systems; Agency for Healthcare Research and Quality; and Texas Transportation Institute. Years in which the data were collected are indicated with the measure. Information is available for metropolitan areas. The website does not indicate when the data are updated.

  7. E

    Diversity in Tech Statistics 2024 – By Countries, Companies And Demographic...

    • enterpriseappstoday.com
    Updated Mar 1, 2024
    + more versions
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    EnterpriseAppsToday (2024). Diversity in Tech Statistics 2024 – By Countries, Companies And Demographic (Age, Gender, Race, Education) [Dataset]. https://www.enterpriseappstoday.com/stats/diversity-in-tech-statistics.html
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    Dataset updated
    Mar 1, 2024
    Dataset authored and provided by
    EnterpriseAppsToday
    License

    https://www.enterpriseappstoday.com/privacy-policyhttps://www.enterpriseappstoday.com/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    Global
    Description

    Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

  8. d

    2020 - 2021 Diversity Report

    • catalog.data.gov
    • data.cityofnewyork.us
    • +1more
    Updated Nov 29, 2024
    + more versions
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    data.cityofnewyork.us (2024). 2020 - 2021 Diversity Report [Dataset]. https://catalog.data.gov/dataset/2020-2021-diversity-report
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    Dataset updated
    Nov 29, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    Report on Demographic Data in New York City Public Schools, 2020-21Enrollment counts are based on the November 13 Audited Register for 2020. Categories with total enrollment values of zero were omitted. Pre-K data includes students in 3-K. Data on students with disabilities, English language learners, and student poverty status are as of March 19, 2021. Due to missing demographic information in rare cases and suppression rules, demographic categories do not always add up to total enrollment and/or citywide totals. NYC DOE "Eligible for free or reduced-price lunch” counts are based on the number of students with families who have qualified for free or reduced-price lunch or are eligible for Human Resources Administration (HRA) benefits. English Language Arts and Math state assessment results for students in grade 9 are not available for inclusion in this report, as the spring 2020 exams did not take place. Spring 2021 ELA and Math test results are not included in this report for K-8 students in 2020-21. Due to the COVID-19 pandemic’s complete transformation of New York City’s school system during the 2020-21 school year, and in accordance with New York State guidance, the 2021 ELA and Math assessments were optional for students to take. As a result, 21.6% of students in grades 3-8 took the English assessment in 2021 and 20.5% of students in grades 3-8 took the Math assessment. These participation rates are not representative of New York City students and schools and are not comparable to prior years, so results are not included in this report. Dual Language enrollment includes English Language Learners and non-English Language Learners. Dual Language data are based on data from STARS; as a result, school participation and student enrollment in Dual Language programs may differ from the data in this report. STARS course scheduling and grade management software applications provide a dynamic internal data system for school use; while standard course codes exist, data are not always consistent from school to school. This report does not include enrollment at District 75 & 79 programs. Students enrolled at Young Adult Borough Centers are represented in the 9-12 District data but not the 9-12 School data. “Prior Year” data included in Comparison tabs refers to data from 2019-20. “Year-to-Year Change” data included in Comparison tabs indicates whether the demographics of a school or special program have grown more or less similar to its district or attendance zone (or school, for special programs) since 2019-20. Year-to-year changes must have been at least 1 percentage point to qualify as “More Similar” or “Less Similar”; changes less than 1 percentage point are categorized as “No Change”. The admissions method tab contains information on the admissions methods used for elementary, middle, and high school programs during the Fall 2020 admissions process. Fall 2020 selection criteria are included for all programs with academic screens, including middle and high school programs. Selection criteria data is based on school-reported information. Fall 2020 Diversity in Admissions priorities is included for applicable middle and high school programs. Note that the data on each school’s demographics and performance includes all students of the given subgroup who were enrolled in the school on November 13, 2020. Some of these students may not have been admitted under the admissions method(s) shown, as some students may have enrolled in the school outside the centralized admissions process (via waitlist, over-the-counter, or transfer), and schools may have changed admissions methods over the past few years. Admissions methods are only reported for grades K-12. "3K and Pre-Kindergarten data are reported at the site level. See below for definitions of site types included in this report. Additionally, please note that this report excludes all students at District 75 sites, reflecting slightly lower enrollment than our total of 60,265 students

  9. View of brands as responsible for boosting diversity in the U.S. 2023, by...

    • ai-chatbox.pro
    • statista.com
    Updated Aug 8, 2024
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    J. G. Navarro (2024). View of brands as responsible for boosting diversity in the U.S. 2023, by generation [Dataset]. https://www.ai-chatbox.pro/?_=%2Ftopics%2F10215%2Fadvertising-and-marketing-to-generation-z-in-the-united-states%2F%23XgboD02vawLKoDs%2BT%2BQLIV8B6B4Q9itA
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    Dataset updated
    Aug 8, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    J. G. Navarro
    Area covered
    United States
    Description

    During an April 2023 survey in the United States, 70 percent of adult respondents who were part of Generation Z (born between 2005 and 2012) reported thinking that brands with a large target audience were either somewhat or very responsible for promoting diversity and inclusion. Among baby boomers (born between 1946 and 1964), that share stood at 64 percent.

  10. Racial diversity in the total workforce of the largest U.S. banks 2023

    • statista.com
    Updated Jun 27, 2025
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    Statista (2025). Racial diversity in the total workforce of the largest U.S. banks 2023 [Dataset]. https://www.statista.com/statistics/1320754/racial-diversity-total-workforce-leading-banks/
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    Except for JPMorgan Chase, Citigroup, Capital One and Bank of America, the share of minority employees in the total U.S.-based workforce of the leading U.S. banks was less than ** percent. Among the observed banks, JPMorgan Chase had the most diverse workforce, with ** percent of the employees who self-identified were racial minorities. JPMorgan Chase was followed by Citigroup, where the share of people of color was approximately ** percent. Capital One ranked third in terms of racial diversity. Here, the share of non-white employees in the U.S.-based workforce was **** percent. The share was the lowest at PNC Financial Services, where approximately ** percent of the workforce were non-white.

  11. Views on racial diversity in ads in U.S. 2020, by ethnicity

    • statista.com
    Updated Aug 9, 2023
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    Statista (2023). Views on racial diversity in ads in U.S. 2020, by ethnicity [Dataset]. https://www.statista.com/statistics/1143034/opinions-racial-diversity-ads-usa-ethnicity/
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    Dataset updated
    Aug 9, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 18, 2020 - Jun 21, 2020
    Area covered
    United States
    Description

    Ethnic minorities were more likely to be in favor of racially diversifying adverts in the United States, a survey from June 2020 found. The African American demographic was most in favor of change, with 65 percent of respondents in saying they would like to see more racial diversity in ads. The same was true for 49 percent of Hispanics in the country.

  12. American Mosaic Project - A National Survey on Diversity

    • thearda.com
    • osf.io
    Updated Nov 14, 2010
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    The Association of Religion Data Archives (2010). American Mosaic Project - A National Survey on Diversity [Dataset]. http://doi.org/10.17605/OSF.IO/A4YGS
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    Dataset updated
    Nov 14, 2010
    Dataset provided by
    Association of Religion Data Archives
    Dataset funded by
    Edelstein Family Foundation
    Description

    The American Mosaic Project is a multiyear, multi-method study of the bases of solidarity and diversity in American life. The principal investigators of this project are Doug Hartmann, Penny Edgell and Joseph Gerteis at the "https://twin-cities.umn.edu/" Target="_blank">University of Minnesota. The survey portion of the project consists of a random-digit-dial telephone survey (N=2,081) conducted during the summer of 2003 by the "https://uwsc.wisc.edu/" Target="_blank">University of Wisconsin Survey Center. The survey was designed to gather data on attitudes about race, religion, politics and American identity as well as demographic information and social networks.

  13. d

    Replication data for: The Diversity Discount: When Increasing Ethnic and...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 20, 2023
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    Daniel J. Hopkins (2023). Replication data for: The Diversity Discount: When Increasing Ethnic and Racial Diversity Prevents Tax Increases [Dataset]. http://doi.org/10.7910/DVN/7TMS4E
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    Dataset updated
    Nov 20, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Daniel J. Hopkins
    Description

    According to recent research, racial and ethnic diversity reduces U.S. localities' investment in public goods. Yet we remain unsure about the mechanisms behind that relationship, and uncertain that the relationship is causal. This essay addresses these challenges by studying the impact of racial and ethnic demographics on property tax votes in Massachusetts and Texas. Employing novel time-series cross-sectional data, it departs from the emerging consensus by showing that diversity does not always influence local tax votes. Instead, diversity reduces localities' willingness to raise taxes only when localities are undergoing sudden demographic changes. Theoretically, this finding points us away from the dominant understanding of diversity as divergent preferences, and towards approaches that emphasize how sudden demographic changes can destabilize residents' expectations and influence local elites. To understand how diversity influences public good provision, we should look to those towns that are diversifying, not those towns that are diverse.

  14. p

    Trends in Diversity Score (2007-2023): Academy Of American Studies vs. New...

    • publicschoolreview.com
    + more versions
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    Public School Review, Trends in Diversity Score (2007-2023): Academy Of American Studies vs. New York vs. New York City Geographic District #30 School District [Dataset]. https://www.publicschoolreview.com/academy-of-american-studies-profile
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    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New York
    Description

    This dataset tracks annual diversity score from 2007 to 2023 for Academy Of American Studies vs. New York and New York City Geographic District #30 School District

  15. u

    An experienced racial-ethnic diversity dataset in the United States using...

    • knowledge.uchicago.edu
    Updated Jul 26, 2023
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    Xu, Wenfei; Wang, Zhuojun; Attia, Nada; Attia, Youssef; Zhang, Yucheng; Zong, Haotian (2023). An experienced racial-ethnic diversity dataset in the United States using human mobility data [Dataset]. http://doi.org/10.17605/OSF.IO/X94GJ
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    Dataset updated
    Jul 26, 2023
    Dataset provided by
    OSF
    Authors
    Xu, Wenfei; Wang, Zhuojun; Attia, Nada; Attia, Youssef; Zhang, Yucheng; Zong, Haotian
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    This national, tract-level experienced racial segregation dataset uses data for over 66 million anonymized and opted-in devices in Cuebiq’s Spectus Clean Room data to estimate 15 minute time overlaps of device stays in 38.2m x 19.1m grids across the United States in 2022. We infer a probability distribution of racial backgrounds for each device given their home Census block groups at the time of data collection, and calculate the probability of a diverse social contact during that space and time. These measures are then aggregated to the Census tract and across the whole time period in order to preserve privacy and develop a generalizable measure of the diversity of a place. We propose that this dataset is a better measurement of the segregation and diversity as it is experienced, which we show diverges from standard measurements of segregation. The data can be used by researchers to better understand the determinants of experienced segregation; beyond research, we suggest this data can be used by policy makers to understand the impacts of policies designed to encourage social mixing and access to opportunities such as affordable housing and mixed-income housing, and more.

    For the purposes of enhanced privacy, home census block groups were pre-calculated by the data provider, and all calculations are done at the Census tract, with tracts that have more than 20 unique devices over the period of analysis.

  16. G

    US NED Topographic Diversity

    • developers.google.com
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    Conservation Science Partners, US NED Topographic Diversity [Dataset]. https://developers.google.com/earth-engine/datasets/catalog/CSP_ERGo_1_0_US_topoDiversity
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    Dataset provided by
    Conservation Science Partners
    Time period covered
    Jan 24, 2006 - May 13, 2011
    Area covered
    Description

    Topographic diversity (D) is a surrogate variable that represents the variety of temperature and moisture conditions available to species as local habitats. It expresses the logic that a higher variety of topo-climate niches should support higher diversity (especially plant) and support species persistence given climatic change. To calculate D, the multi-scale Topographic Position Index (mTPI), being a dominant control of soil moisture (T), was used for measuring hillslope position. The mTPI was combined with the square-root transform for mTPI>0 (T') and with the standard deviation of the Continuous Heat-Insolation Load Index (CHILI), calculated at multiple scales (C') as: D = 1 - ((1-T') * (1-C'). It is based on the USGS's 10m NED DEM (available in EE as USGS/NED). The Conservation Science Partners (CSP) Ecologically Relevant Geomorphology (ERGo) Datasets, Landforms and Physiography contain detailed, multi-scale data on landforms and physiographic (aka land facet) patterns. Although there are many potential uses of these data, the original purpose for these data was to develop an ecologically relevant classification and map of landforms and physiographic classes that are suitable for climate adaptation planning. Because there is large uncertainty associated with future climate conditions and even more uncertainty around ecological responses, providing information about what is unlikely to change offers a strong foundation for managers to build robust climate adaptation plans. The quantification of these features of the landscape is sensitive to the resolution, so we provide the highest resolution possible given the extent and characteristics of a given index.

  17. p

    Trends in Diversity Score (2011-2023): American Preparatory Academy - The...

    • publicschoolreview.com
    Updated Feb 9, 2025
    + more versions
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    Public School Review (2025). Trends in Diversity Score (2011-2023): American Preparatory Academy - The School For New Americans vs. Utah vs. American Preparatory Academy School District [Dataset]. https://www.publicschoolreview.com/american-preparatory-academy-the-school-for-new-americans-profile
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    Dataset updated
    Feb 9, 2025
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    This dataset tracks annual diversity score from 2011 to 2023 for American Preparatory Academy - The School For New Americans vs. Utah and American Preparatory Academy School District

  18. N

    United States annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). United States annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/bacb49c0-f4ce-11ef-8577-3860777c1fe6/
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    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    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 United States. The dataset can be utilized to gain insights into gender-based income distribution within the United States population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within United States, among individuals aged 15 years and older with income, there were 119.64 million men and 117.56 million women in the workforce. Among them, 66.07 million men were engaged in full-time, year-round employment, while 50.33 million women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 7.45% fell within the income range of under $24,999, while 10.76% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 29.72% of men in full-time roles earned incomes exceeding $100,000, while 18.56% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for United States median household income by race. You can refer the same here

  19. e

    Race in the US by Dot Density

    • coronavirus-resources.esri.com
    • coronavirus-disasterresponse.hub.arcgis.com
    Updated Jan 10, 2020
    + more versions
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    ArcGIS Living Atlas Team (2020). Race in the US by Dot Density [Dataset]. https://coronavirus-resources.esri.com/maps/71df79b33d4e4db28c915a9f16c3074e
    Explore at:
    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This map is designed to work in the new ArcGIS Online Map Viewer. Open in Map Viewer to view map. What does this map show?This map shows the population in the US by race. The map shows this pattern nationwide for states, counties, and tracts. Open the map in the new ArcGIS Online Map Viewer Beta to see the dot density pattern. What is dot density?The density is visualized by randomly placing one dot per a given value for the desired attribute. Unlike choropleth visualizations, dot density can be mapped using total counts since the size of the polygon plays a significant role in the perceived density of the attribute.Where is the data from?The data in this map comes from the most current American Community Survey (ACS) from the U.S. Census Bureau. Table B03002. The layer being used if updated with the most current data each year when the Census releases new estimates. The layer can be found in ArcGIS Living Atlas of the World: ACS Race and Hispanic Origin Variables - Boundaries.What questions does this map answer?Where do people of different races live?Do people of a similar race live close to people of their own race?Which cities have a diverse range of different races? Less diverse?

  20. p

    Trends in Diversity Score (2017-2023): American Academy Of Innovation School...

    • publicschoolreview.com
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    Public School Review, Trends in Diversity Score (2017-2023): American Academy Of Innovation School District vs. Utah [Dataset]. https://www.publicschoolreview.com/utah/american-academy-of-innovation-school-district/4900186-school-district
    Explore at:
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset tracks annual diversity score from 2017 to 2023 for American Academy Of Innovation School District vs. Utah

Share
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Statista (2025). U.S. adults' beliefs on increasing diversity at work 2023, by race [Dataset]. https://www.statista.com/statistics/1391380/us-adults-beliefs-on-increasing-diversity-at-work-by-race/
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U.S. adults' beliefs on increasing diversity at work 2023, by race

Explore at:
Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Feb 6, 2023 - Feb 12, 2023
Area covered
United States
Description

According to a survey conducted in 2023, ** percent of employed adults who were Black believed that focusing on increasing diversity, equity, and inclusion at work was a good thing in the United States, while ** percent of employed adults who were White shared this belief.

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