About this dataset

Context

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

Key observations

The percent distribution of San Jose population by race (across all racial categories recognized by the U.S. Census Bureau): 29.01% are white, 2.91% are Black or African American, 1.01% are American Indian and Alaska Native, 38.58% are Asian, 0.50% are Native Hawaiian and other Pacific Islander, 13.62% are some other race and 14.37% 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 San Jose
• Population: The population of the racial category (excluding ethnicity) in the San Jose is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of San Jose 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 San Jose Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in San Jose, the largest racial group is White alone with a population of 517 (86.17% of the total Non-Hispanic population).

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, Two or More Races (5-year estimate) in Santa Clara County, CA (B03002009E006085) from 2009 to 2023 about Santa Clara County, CA; San Jose; CA; non-hispanic; estimate; persons; 5-year; population; and USA.

Graph and download economic data for Population Estimate, Total, Hispanic or Latino, Two or More Races, Two Races Including Some Other Race (5-year estimate) in San Benito County, CA (B03002020E006069) from 2009 to 2023 about San Benito County, CA; San Jose; latino; hispanic; CA; estimate; persons; 5-year; population; and USA.

This dataset provides a framework for prioritizing investments from an equity standpoint using a simple scoring system. The index generates scores in four component areas: race (percent BIPOC), income (median household income), language (percent limited English proficiency), and education (percent of adults with less than HS diploma or equivalent). Each component score is on a scale of 1 (low priority) to 5 (high priority), where each value (1-5) covers approximately 20 percent of the population. A combined score is also provided in the EQUITYSCORECOMBINED field. The combined score is the sum of the race and income scores and is based on a scale of 2 to 10. The combined score has been adopted as the standard equity score. Language and education scores are provided for reference only and do not factor into the combined score.

Historical Dataset of San Jose High School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1990-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1990-2023),American Indian Student Percentage Comparison Over Years (1989-2014),Asian Student Percentage Comparison Over Years (1991-2023),Hispanic Student Percentage Comparison Over Years (1991-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Native Hawaiian or Pacific Islander Student Percentage Comparison Over Years (2011-2014),Two or More Races Student Percentage Comparison Over Years (2009-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (1992-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2002-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2012-2023),Overall School Rank Trends Over Years (2012-2023),Graduation Rate Comparison Over Years (2013-2023)

This dataset tracks annual two or more races student percentage from 2009 to 2023 for San Jose High School vs. California and San Jose Unified School District

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED September 2016

DESCRIPTION
Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES
U.S. Census Bureau 1960-1990 Decennial Census http://factfinder2.census.gov

California Department of Finance 1961-2016 Population and Housing Estimates http://www.dof.ca.gov/research/demographic/

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, tract) are as of January 1, 2010, released beginning November 30, 2010 by the U.S. Census Bureau. A priority development area (PDA) is a locally-designated infill area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are as current as July 2016. Population estimates for PDAs were derived from Census population counts at the block group level for 2000-2014 and at the tract level for 1970-1990.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average). Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average.

Estimates of density for tracts and PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside InlandCoastalDelta: American Canyon, Benicia, Clayton, Concord, Cotati, Danville, Dublin, Lafayette, Martinez, Moraga, Napa, Novato, Orinda, Petaluma, Pleasant Hill, Pleasanton, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Walnut Creek, Antioch, Brentwood, Calistoga, Cloverdale, Dixon, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Livermore, Morgan Hill, Oakley, Pittsburg, Rio Vista, Sonoma, St. Helena, Suisun City, Vacaville, Windsor, Yountville Unincorporated: all unincorporated towns

About this dataset

Context

The dataset tabulates the San Jose population by race and ethnicity. The dataset can be utilized to understand the racial distribution of San Jose.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• San Jose, CA Population Breakdown by Race
• San Jose, CA Non-Hispanic Population Breakdown by Race
• San Jose, CA Hispanic or Latino Population Distribution by Their Ancestries

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/.

computer-assisted personal interview (CAPI); computer-assisted telephone interview (CATI)This data collection was previously distributed by the National Endowment for the Arts (NEA) from their website. The SPPA 2012 was originally released in September 2013. This previous release has been revised to reflect changes in how the 2012 SPPA counted "interviews." Specifically, the Census revisions count "yes," "no," and "don't know" as interviews, in accordance with estimates generated from the 2008 and earlier waves of the SPPA. Alternatively, the September 2013 estimates provided by the U.S. Census Bureau had included respondents who "refused to answer" as interviews--an action that clouded comparisons with previous SPPA waves. Many of the 2012 SPPA estimates were unaffected by these revisions. And of those that were affected, most changes to participation rates were marginal, often in the range of 1-2 tenths of a percentage point. Users are strongly encouraged to refer the CPS User Guide (produced by the Census Bureau), which contains additional detailed technical documentation regarding the CPS study design, sampling frame used, and response rates. Users are also encouraged to read the SPPA User Guide (produced by the Urban Institute) for information about the SPPA, including the design, dealing with missing respondent data, weights, and multi-variable analysis.The universe statements for each variable are defined in the basic or supplement record layouts found in Attachment 6 and 7, respectively, of the CPS User Guide. The SPPA provides estimates for 32 states: Alabama; California; Colorado, Connecticut; Florida; Georgia; Illinois; Iowa; Kansas; Maine; Maryland; Massachusetts; Michigan; Minnesota; Missouri; Nebraska; Nevada; New Jersey; New York; North Carolina; North Dakota; Ohio; Oregon; Pennsylvania; Rhode Island; South Carolina; South Dakota; Texas; Virginia; Washington; West Virginia; and Wyoming. In addition, the SPPA can reliably supply arts participation estimates for 11 metropolitan areas: Boston-Worchester-Manchester, MA-NH; Chicago-Naperville-Michigan City, IL-IN; Dallas-Fort Worth, TX; Denver-Aurora-Boulder, CO; Detroit-Warren-Flint, MI; Los Angeles-Long Beach-Riverside, CA; Miami-Fort Lauderdale-Miami Beach, FL; New York-Newark-Bridgeport, NY-NJ-CT-PA; Philadelphia-Camden-Vineland, PA-NJ-DE-MD; San Jose-Francisco-Oakland, CA; and Washington-Baltimore-Northern Virginia, DC-MD-VA-WV. Users cannot do analysis that combines variables from Core 1 and Core 2 because respondents were assigned to either complete Core 1 or Core 2, but never Core 1 and Core 2. Also, analyses cannot use variables from more than two modules in the same runs since no respondent answered more than 2 modules. So doing such analyses can raise sample size concerns.Users must use appropriate weights to analyze the SPPA 2012 data. For online analysis, subsets of the data were created, each with the variables that need to be used with the 1 SPPA weight variable. The Part 2 dataset contains CPS variables and SPPA Core 1 questions including those about asked respondents' and their spouse/partners' artistic activity and frequency of participation in the past year. The Part 3 dataset contains CPS variables and SPPA Core 2 experimental questions including those about asked respondents' and their spouse/partners' artistic activity and frequency of participation in the past year. The Part 4 dataset contains CPS variables and SPPA modules A1 and D questions that asked respondents and their spouse/partners about reading, film, and sporting event attendance as well as creating, performing, and other artistic activities in the past year. The Part 5 dataset contains CPS variables and SPPA Module A2 questions that asked respondents about other live performances attendances and music listening preferences in the past year. The Part 6 dataset contains CPS variables and Modules B, C, and E questions including those that asked respondents about accessing art through media and frequency of participation through the media in the past year, creating arts through the media in the past year, and participation in arts education in the past year.The "PC" variables (e.g. JAZZ_PC) should be used to match the SPPA 2012 published results.Information regarding data processing for this data collection is in the "Codebook Notes" page(s) in the ICPSR Codebook. Most notably: For this data collection, ICPSR created the CASEID variable which is a unique case identifier. The "Basic CPS Record Layout" section in the CPS User Guide (see Attachment 6) contains many FILLER variables and a couple PADDING variables with column locations. Also, only 1 FILLER variable was found in the data that ICPSR received, and ICPSR removed the FILLER variable. As a result, the column locations in any ICPSR-released data product (e.g., codebook and setup files) will have column locations that are not consistent with locations described in the CPS User Guide. Please note that miss...

VITAL SIGNS INDICATOR Time Spent In Congestion (T7)

FULL MEASURE NAME Congested delay on regional freeways

LAST UPDATED May 2017

DESCRIPTION Time spent in traffic congestion – also known as congested delay – refers to the number of minutes weekday travelers spend in congested conditions in which freeway speeds drop below 35 mph. Total delay, a companion measure, includes both congested delay and all other delay in which speeds are below the posted speed limit.

DATA SOURCE Metropolitan Transportation Commission: Historical Congestion Analysis

California Department of Finance Forms E-5 and E-8 http://www.dof.ca.gov/research/demographic/reports/estimates/e-8/ http://www.dof.ca.gov/research/demographic/reports/estimates/e-5/2011-20/view.php

California Employment Development Department: Labor Market Information http://www.labormarketinfo.edd.ca.gov/

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Delay statistics only include freeway facilities and rely upon INRIX traffic data. They reflect delay on a typical weekday, which is defined as Tuesday through Thursday during peak traffic months. Delay statistics emphasize recurring delay - i.e. consistent delay greater than 15 minutes on a specific freeway segment. Congested delay is defined as congestion occurring with speeds less than 35 mph and is commonly recognized as inefficient delay (meaning that the freeway corridor is operating at speeds low enough to reduce throughput - as opposed to speeds greater than 35 mph which increase throughput). Data sources listed above were used to calculate per-capita and per-worker statistics; national datasets were used for metro comparisons and California datasets were used for the Bay Area. Top congested corridors are ranked by total vehicle hours of delay, meaning that the highlighted corridors reflect a combination of slow speeds and heavy traffic volumes. Historical Bay Area data was estimated by MTC Operations staff using a combination of internal datasets to develop an approximate trend back to 1998. The metropolitan area comparison was performed for the combined primary urbanized areas (San Francisco-Oakland and San Jose) as well as nine other major metropolitan areas' core urbanized area. Because the Texas Transportation Institute no longer reports congested freeway delay or total freeway delay (focusing solely on total regional delay), 2011 data was used to estimate 2014 total freeway delay for each metro area by relying upon the freeway-to-regional ratio from 2011. Estimated urbanized area workers were used for this analysis using the 2011 ratios, which accounts for slight differentials between Bay Area data points under the regional historical data and the metro comparison analysis. To explore how 2016 congestion trends compare to real-time congestion on the region’s freeways, visit 511.org.

About this dataset

Context

The dataset tabulates the San Jose population by race and ethnicity. The dataset can be utilized to understand the racial distribution of San Jose.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• San Jose, IL Population Breakdown by Race
• San Jose, IL Non-Hispanic Population Breakdown by Race
• San Jose, IL Hispanic or Latino Population Distribution by Their Ancestries

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/.

About this dataset

Context

The dataset tabulates the San Jose Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of San Jose, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of San Jose.

Key observations

Among the Hispanic population in San Jose, regardless of the race, the largest group is of Mexican origin, with a population of 251,964 (82.22% of the total Hispanic population).

Content

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

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the San Jose
• Population: The population of the specific origin for Hispanic or Latino population in the San Jose is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of San Jose total Hispanic or Latino 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 San Jose Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the San Jose median household income by race. The dataset can be utilized to understand the racial distribution of San Jose income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• San Jose, IL median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in San Jose, IL (2021, in 2022 inflation-adjusted dollars)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of San Jose median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in San Jose. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In San Jose, the median household income for the households where the householder is White decreased by $7,678(11.16%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $68,789 in 2013 and $61,111 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in San Jose, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

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 of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in San Jose.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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 San Jose median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in San Jose. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of San Jose population by race & ethnicity, the population is predominantly Asian. This particular racial category constitutes the majority, accounting for 38.58% of the total residents in San Jose. Notably, the median household income for Asian households is $179,214. Interestingly, Asian is both the largest group and the one with the highest median household income, which stands at $179,214.

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 of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in San Jose.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 San Jose median household income by race. You can refer the same here

About this dataset

Context

The dataset tabulates the population of San Jose by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of San Jose across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 52.98% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the San Jose is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of San Jose 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 San Jose Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the San Jose population by year. The dataset can be utilized to understand the population trend of San Jose.

Content

The dataset constitues the following datasets

• San Jose, CA Population Dataset: Yearly Figures, Population Change, and Percent Change Analysis

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/.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in San Jose. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In San Jose, the median income for all workers aged 15 years and older, regardless of work hours, was $37,188 for males and $32,750 for females.

Based on these incomes, we observe a gender gap percentage of approximately 12%, indicating a significant disparity between the median incomes of males and females in San Jose. Women, regardless of work hours, still earn 88 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.21 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

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.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 San Jose median household income by race. You can refer the same here