- 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 $37,369 in 2017.
Earnings and Gender
Earnings and Education
Jobs and Earnings Datasets Involving Alaska
- API opendata.ramseycounty.us | Last Updated 2019-02-08T22:23:58.000Z
Dataset showing average income for households and individuals by race and ethnicity.
- API opendata.ramseycounty.us | Last Updated 2017-08-11T13:25:58.000Z
Dataset showing the average income in dollars per capita by race and ethnicity.
- API opendata.utah.gov | Last Updated 2014-10-31T18:29:13.000Z
Median Household Income All States 2000-2012
- API data.vbgov.com | Last Updated 2017-10-12T13:51:45.000Z
This dataset provides demographic information from the American Community Survey about residents of Virginia Beach. This data was originally provided in the executive summary of the City of Virginia Beach’s Operating Budget.
- API data.iowa.gov | Last Updated 2019-03-05T22:47:57.000Z
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 2018-07-25T18:50:47.000Z
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 opendata.usac.org | Last Updated 2019-02-25T11:05:44.000Z
This dataset provides information about total dollars disbursed to Eligible Telecommunication Carriers (ETCs) within the High Cost Program by month and year since January 2003.
- API data.imls.gov | Last Updated 2017-09-07T15:48:11.000Z
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 opendata.ci.richmond.ca.us | Last Updated 2017-01-25T20:58:31.000Z
Census data from Bay Area Census and US Census.
- API opendata.maryland.gov | Last Updated 2018-02-27T16:43:52.000Z
Maryland county data for population, gender, race, labor force, educational attainment, income, poverty, households and housing units. Data Source: 2012 -2016 American Community Survey, 5 Year estimates. U.S. Census Bureau, released December 2017. Is updated annually for the 5 year period.