- What is the Percent who did not finish the 9th grade?
- What is the Percent with an associate's degree?
- What is the College Graduation Rate?
- What is the Percent with a graduate or professional degree?
- What is the Population Count?
- What is the Population Density?
- What is the Land Area?
- What is the Student Teacher Ratio?
- What is the Median Earnings?
- What is the Mean Job Proximity Index?
The high school graduation rate of Honolulu County, HI was 90.30% in 2013.
Education and Graduation Rates Datasets Involving Honolulu County, HI
- API dashboard.hawaii.gov | Last Updated 2013-11-11T17:47:08.000Z
Individuals served by the Homeless Shelter Program.
- API data.hawaii.gov | Last Updated 2015-10-27T00:16:12.000Z
* Fall headcount of credit students, includes special students (early admits and concurrent registrants) for all years shown * Unclassified at UH Manoa includes no data on educational level. Source: University of Hawai'i, Institutional Research and Analysis Office, records.
- API dashboard.hawaii.gov | Last Updated 2013-04-04T17:21:43.000Z
- API data.hawaii.gov | Last Updated 2012-09-27T02:22:13.000Z
The Hawai'i Directory of Green Employers is a growing online directory of green employers in Hawai'i. The Hawaii Department of Labor and Industrial Relations (DLIR) defines green employers as businesses that employ workers in occupations in these core areas: • Generate clean, renewable, sustainable Energy • Reduce pollution and waste; conserve natural resources; recycle • Energy efficiency • Education, training and support of green workforce • Natural, sustainable, environmentally-friendly production The Directory contains employers’ self-posted profiles that describe their operations, specify their core occupations, and describe the skills and education they want in employees. Jobseekers, students, their counselors and advisors, and others can access the employer profiles to learn about these companies and the workers they require.
- API dashboard.hawaii.gov | Last Updated 2014-12-31T05:16:35.000Z
- API data.ny.gov | Last Updated 2016-09-19T19:08:40.000Z
Under New York State’s Hate Crime Law (Penal Law Article 485), a person commits a hate crime when one of a specified set of offenses is committed targeting a victim because of a perception or belief about their race, color, national origin, ancestry, gender, religion, religious practice, age, disability, or sexual orientation, or when such an act is committed as a result of that type of perception or belief. These types of crimes can target an individual, a group of individuals, or public or private property. DCJS submits hate crime incident data to the FBI’s Uniform Crime Reporting (UCR) Program. Information collected includes number of victims, number of offenders, type of bias motivation, and type of victim.
- API data.hawaii.gov | Last Updated 2012-09-04T21:57:28.000Z
Listing of the Public Libraries in the State of Hawaii
- API data.hawaii.gov | Last Updated 2013-02-06T23:05:42.000Z
1/ Historical labor force and jobs data revised. For details, see Hawaii DLIR <http://www.hiwi.org/cgi/dataanalysis/?PAGEID=94> . 2/ Data from January 1999 have been revised and consist of domestic and international air arrivals. They are not comparable to Eastbound and Westbound series. Source: Hawaii Department of Labor & Industrial Relations; Hawaii Department of Taxation; Hawaii Department of Business, Economic Development and Tourism; county building departments; Honolulu Board of REALTORS® compiled by Harvey Shapiro, Title Guaranty of Hawaii and Realtors® Association of Maui, Inc. Final tables compiled by Statistics and Data Support Branch, READ, DBEDT
- API data.ny.gov | Last Updated 2017-09-21T14:31:42.000Z
The number of persons described by survey year (2013) reported in OMH Region-specific totals (Region of Provider) and three demographic characteristics of the client served during the week of the survey: gender (Male, Female,Transgender Male, Transgender Female), age (below 5,5–12, 13–17, 18–20, 21–34, 35–44, 45–64, 65–74, 75 and above, and unknown age) and race (White only, Black/ African American Only, Multi-racial, Other and unknown race) and ethnicity (Non-Hispanic, Hispanic, and Unknown). Persons with Hispanic ethnicity are grouped as “Hispanic,” regardless of race or races reported.
- 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.