The percent with an associate's degree of Bethel Census Area, AK was 3.90% in 2016. The percent with an associate's degree of Jefferson County, OR was 9.50% in 2016.
Education and Graduation Rates Datasets Involving Jefferson County, OR or Bethel Census Area, AK
- API data.oregon.gov | Last Updated 2018-06-01T23:40:31.000Z
This data was provided by the Oregon Department of Education. For more information contact them directly through the following link. (https://www.oregon.gov/ode/Pages/default.aspx). Note: For this time period, actual expenditures for operating funds (General, Special Revenue, Enterprise and Food Services Funds) per student.and student count for enrollment as of October 1 was provided.
- API data.acgov.org | Last Updated 2016-02-04T20:06:11.000Z
US Census 2010 Poverty Statistics Alameda County by Census Tract
- API data.orcities.org | Last Updated 2017-01-06T16:41:02.000Z
Data from the American Community Survey 2014 on all LOC member cities. This dataset includes select information for education, health and transportation statistics.
- API chhs.data.ca.gov | Last Updated 2017-06-14T18:11:25.000Z
This table contains data on the percent of residents aged 25 years and older educational attainment (percent completing high school, associates degree, college or more advanced degree) for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and 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 (https://www.cdph.ca.gov/Programs/OHE/Pages/Healthy-Communities-Data-and-Indicators-Project-(HCI).aspx). Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information about the data table and a data dictionary can be found in the About/Attachments section.
- API bronx.lehman.cuny.edu | Last Updated 2013-06-10T03:17:53.000Z
Results from the 2010 Census regard ethnic makeup of Bronx census tracts. Source of this data came from the faculty of the Geography department at Lehman College
- 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.
- 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.ramseycounty.us | Last Updated 2017-08-10T19:18:13.000Z
Dataset showing the percent of residents in poverty by county. Following the Office of Management and Budget’s (OMB’s) Directive 14, the Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If the total income for a family or unrelated individual falls below the relevant poverty threshold, then the family (and every individual in it) or unrelated individual is considered in poverty.
- API data.oregon.gov | Last Updated 2015-10-27T22:06:38.000Z
Data is collected annually and adjusted for inflation using the GDP Deflator.
- 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.