- What is the Population Rate of Change?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Total Administration Salaries?
- What is the Student Teacher Ratio?
- What is the Median Earnings?
- What is the Number of Employees?
- What is the Percent Without Health Insurance?
- What is the Access to Exercise Opportunities Rate?
The population count of Alaska was 736,855 in 2016.
Demographics and Population Datasets Involving Alaska
- API data.livewellsd.org | Last Updated 2017-09-10T03:32:38.000Z
The number and percent of the population stratified by race/ethnicity. API refers to Asian/ Pacific Islanders and include Asian, Pacific Islander, and Native Hawaiian. Other Race includes American Indian or Alaska Native, 2 or more races, and other. Source: U.S. Census Bureau; 2011-2015 American Community Survey 5-Year Estimates, Table B03002.
- API data.govloop.com | Last Updated 2011-08-21T02:51:18.000Z
Number and percentage of minorities that work in federal government. Black, hispanic, asian, and white
- 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 opendata.ramseycounty.us | Last Updated 2017-08-10T19:21:17.000Z
Dataset showing responses to questions on race and ethnicity. The data on race were derived from answers to the question on race that was asked of all people during the decennial (every ten years) Census. The U.S. Census Bureau collects race data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country, and not an attempt to define race biologically, anthropologically, or genetically. In addition, it is recognized that the categories of the race item include racial and national origin or socio-cultural groups. Definitions from OMB guide the Census Bureau in classifying written responses to the race question: White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander Some Other Race Two or More Races There are two minimum categories for ethnicity: Hispanic or Latino and Not Hispanic or Latino. The federal government considers race and Hispanic origin to be two separate and distinct concepts. Hispanics and Latinos may be of any race
- API data.smcgov.org | Last Updated 2016-09-30T03:35:19.000Z
Demographic data for Get Healthy San Mateo County's Healthy Cities SMC: http://www.gethealthysmc.org/healthy-cities-smc
- 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 data.colorado.gov | Last Updated 2014-12-19T21:36:25.000Z
The 2011-12 school year marked the sixth year in which the Colorado Department of Education calculated and reported student mobility rates. In addition, this year the state began reporting stability rates. The stability rate represents the number and percent of students who remained at a school/district without interruption throughout the school year.
- API data.smcgov.org | Last Updated 2017-10-30T22:22:51.000Z
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.nashville.gov | Last Updated 2018-02-13T14:06:15.000Z
This dataset contains a listing of Metro Public Schools (MPS), including adult, alternative learning, charter, elementary, high, middle, non-traditional, non-traditional-hybrid and special education schools with student enrollment and demographic information.
- API data.pa.gov | Last Updated 2017-07-31T18:19:23.000Z
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.