- What is the Median Female Earnings?
- What is the Median Male Earnings?
- What is the Median Female Earnings (Full Time)?
- What is the Median Male Earnings (Full Time)?
- What is the Median Earnings Less Than High School?
- What is the Median Earnings High School?
- What is the Median Earnings Some College or Associates?
- What is the Median Earnings Bachelor Degree?
- What is the Median Earnings Graduate or Professional Degree?
- What is the Percent Earning less than $10,000?
The median earnings of Alaska was $35,169 in 2013.
Earnings and Gender
Earnings and Education
Jobs and Earnings Datasets Involving Alaska
- API chhs.data.ca.gov | Last Updated 2017-02-17T22:39:34.000Z
This table contains data on the living wage and the percent of families with incomes below the living wage for California, its counties, regions and cities/towns. Living wage is the wage needed to cover basic family expenses (basic needs budget) plus all relevant taxes; it does not include publicly provided income or housing assistance. The percent of families below the living wage was calculated using data from the Living Wage Calculator (http://livingwage.mit.edu/) and the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity (http://www.cdph.ca.gov/programs/Pages/HealthyCommunityIndicators.aspx). The living wage is the wage or annual income that covers the cost of the bare necessities of life for a worker and his/her family. These necessities include housing, transportation, food, childcare, health care, and payment of taxes. Low income populations and non-white race/ethnic have disproportionately lower wages, poorer housing, and higher levels of food insecurity. More information about the data table and a data dictionary can be found in the About/Attachments section.
- API opendata.utah.gov | Last Updated 2014-10-31T18:29:13.000Z
Median Household Income All States 2000-2012
- API data.iowa.gov | Last Updated 2017-02-13T21:06:47.000Z
Iowa Vocational Rehabilitation Services mission is to provide expert, individualized services to Iowans with disabilities to achieve their independence through successful employment and economic support. This dataset provides information on closed cases where the individual received services from IVRC. Data includes cases closed after October 1, 2008.
- API data.pa.gov | Last Updated 2016-11-08T20:03:29.000Z
This data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.
- API data.imls.gov | Last Updated 2016-12-07T00:10:49.000Z
Pull up a state's profile to find state-level totals on key data such as numbers of libraries and librarians, revenue and expenditures, and collection sizes.<br><br>These data include imputed values for libraries that did not submit information in the FY 2014 data collection. Imputation is a procedure for estimating a value for a specific data item where the response is missing. <br><br>Download PLS data files to see imputation flag variables or learn more on the imputation methods used in FY 2014 at https://www.imls.gov/research-evaluation/data-collection/public-libraries-survey/explore-pls-data/pls-data
- API churned-data.awcnet.org | Last Updated 2014-11-03T22:01:09.000Z
This dataset provides a number of community indicators related to income, age, diversity, and educational attainment. With the exception of the 2014 Pop. Estimate and Pop. Growth 2000 to Present, indicators are derived from the US Census' American Community Survey 2012 5-year estimates.
- API data.smcgov.org | Last Updated 2015-10-22T16:01:33.000Z
Demographics, including median income, total population, race, ethnicity, and age for unincorporated areas in San Mateo County. This data comes from the 2012 American Community Survey 5 year estimates DP03 and DP05 files. They Sky Londa area is located within two Census Tracts. The data for Sky Londa is the sum of both of those Census Tracts. Users of this data should take this into account when using data for Sky Londa.
- API data.acgov.org | Last Updated 2016-02-04T20:06:11.000Z
US Census 2010 Poverty Statistics Alameda County by Census Tract
- API data.austintexas.gov | Last Updated 2015-06-16T21:27:59.000Z
The 2014 Austin Digital Assessment Project was supported by the Telecommunications & Regulatory Affairs Office of the City of Austin, the Telecommunications and Information Policy Institute at the University of Texas, and faculty and graduate students from the Department of Radio, Television, and Film and the University of Texas. This dataset includes the individual survey responses. To see aggregated dataset weighted to reflect Austin demographics, refer to the attached document.
- API opendata.utah.gov | Last Updated 2015-07-09T00:47:24.000Z
This data set contains median home values, demographic detail, educational levels, population data and other socioeconomic data for counties in Utah. Data is from the US Census Bureau.