- 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 Median Earnings?
- What is the Number of Employees?
- What is the Annual Personal Income?
- What is the Personal Consumption Expenditure?
- What is the Population Rate of Change?
The high school graduation rate of United States was 87.70% in 2018.
Education and Graduation Rates Datasets Involving United States
- API data.cityofchicago.org | Last Updated 2018-09-14T21:38:54.000Z
This dataset shows all school level performance data used to create CPS School Report Cards for the 2011-2012 school year. Metrics are described as follows (also available for download at http://bit.ly/uhbzah): NDA indicates "No Data Available." SAFETY ICON: Student Perception/Safety category from 5 Essentials survey // SAFETY SCORE: Student Perception/Safety score from 5 Essentials survey // FAMILY INVOLVEMENT ICON: Involved Families category from 5 Essentials survey // FAMILY INVOLVEMENT SCORE: Involved Families score from 5 Essentials survey // ENVIRONMENT ICON: Supportive Environment category from 5 Essentials survey // ENVIRONMENT SCORE: Supportive Environment score from 5 Essentials survey // INSTRUCTION ICON: Ambitious Instruction category from 5 Essentials survey // INSTRUCTION SCORE: Ambitious Instruction score from 5 Essentials survey // LEADERS ICON: Effective Leaders category from 5 Essentials survey // LEADERS SCORE: Effective Leaders score from 5 Essentials survey // TEACHERS ICON: Collaborative Teachers category from 5 Essentials survey // TEACHERS SCORE: Collaborative Teachers score from 5 Essentials survey // PARENT ENGAGEMENT ICON: Parent Perception/Engagement category from parent survey // PARENT ENGAGEMENT SCORE: Parent Perception/Engagement score from parent survey // AVERAGE STUDENT ATTENDANCE: Average daily student attendance // RATE OF MISCONDUCTS (PER 100 STUDENTS): # of misconducts per 100 students//AVERAGE TEACHER ATTENDANCE: Average daily teacher attendance // INDIVIDUALIZED EDUCATION PROGRAM COMPLIANCE RATE: % of IEPs and 504 plans completed by due date // PK-2 LITERACY: % of students at benchmark on DIBELS or IDEL // PK-2 MATH: % of students at benchmark on mClass // GR3-5 GRADE LEVEL MATH: % of students at grade level, math, grades 3-5 // GR3-5 GRADE LEVEL READ: % of students at grade level, reading, grades 3-5 // GR3-5 KEEP PACE READ: % of students meeting growth targets, reading, grades 3-5 // GR3-5 KEEP PACE MATH: % of students meeting growth targets, math, grades 3-5 // GR6-8 GRADE LEVEL MATH: % of students at grade level, math, grades 6-8 // GR6-8 GRADE LEVEL READ: % of students at grade level, reading, grades 6-8 // GR6-8 KEEP PACE MATH: % of students meeting growth targets, math, grades 6-8 // GR6-8 KEEP PACE READ: % of students meeting growth targets, reading, grades 6-8 // GR-8 EXPLORE MATH: % of students at college readiness benchmark, math // GR-8 EXPLORE READ: % of students at college readiness benchmark, reading // ISAT EXCEEDING MATH: % of students exceeding on ISAT, math // ISAT EXCEEDING READ: % of students exceeding on ISAT, reading // ISAT VALUE ADD MATH: ISAT value-add value, math // ISAT VALUE ADD READ: ISAT value-add value, reading // ISAT VALUE ADD COLOR MATH: ISAT value-add color, math // ISAT VALUE ADD COLOR READ: ISAT value-add color, reading // STUDENTS TAKING ALGEBRA: % of students taking algebra // STUDENTS PASSING ALGEBRA: % of students passing algebra // 9TH GRADE EXPLORE (2009): Average EXPLORE score, 9th graders who tested in fall 2009 // 9TH GRADE EXPLORE (2010): Average EXPLORE score, 9th graders who tested in fall 2010 // 10TH GRADE PLAN (2009): Average PLAN score, 10th graders who tested in fall 2009 // 10TH GRADE PLAN (2010): Average PLAN score, 10th graders who tested in fall 2010 // NET CHANGE EXPLORE AND PLAN: Difference between Grade 9 Explore (2009) and Grade 10 Plan (2010) // 11TH GRADE AVERAGE ACT (2011): Average ACT score, 11th graders who tested in fall 2011 // NET CHANGE PLAN AND ACT: Difference between Grade 10 Plan (2009) and Grade 11 ACT (2011) // COLLEGE ELIGIBILITY: % of graduates eligible for a selective four-year college // GRADUATION RATE: % of students who have graduated within five years // COLLEGE/ ENROLLMENT RATE: % of students enrolled in college // COLLEGE ENROLLMENT (NUMBER OF STUDENTS): Total school enrollment // FRESHMAN ON TRACK RATE: Freshmen On-Track rate // RCDTS: Region County District Type Schools Code
- API opendata.maryland.gov | Last Updated 2019-12-19T13:22:09.000Z
K-12 and higher education - enrollment, graduates, expenditures, institutions.
- API data.cityofchicago.org | Last Updated 2013-11-26T20:22:07.000Z
This dataset shows the 2012 School Progress Report Card data elements for each CPS high school. The report card is an annual summary of how the school is doing. For more information on the School Progress Report Cards, please see http://cps.edu/Schools/Pages/SchoolProgressReportCards.aspx.
- API opendata.maryland.gov | Last Updated 2019-09-27T14:16:09.000Z
K-12 and higher education - expenditures, institutions, and attainment.
- API data.cityofchicago.org | Last Updated 2018-07-11T20:44:35.000Z
This dataset shows the 2013 School Progress Report Card data elements for each CPS high school. The report card is an annual summary of how the school is doing. For more information on the School Progress Report Cards, please see http://www.cps.edu/SCHOOLDATA/Pages/SchoolProgressReports.aspx
- API data.cityofnewyork.us | Last Updated 2022-02-28T14:48:56.000Z
To understand the perceptions of families, students, and teachers regarding their school. School leaders use feedback from the survey to reflect and make improvements to schools and programs. Also, results from the survey used to help measure school quality. Each year, all parents, teachers, and students in grades 6-12 take the NYC School Survey. The survey is aligned to the DOE's Framework for Great Schools. It is designed to collect important information about each school's ability to support student success. Please note: The larger complete data file is downloadable under the Attachments Section
- API data.ct.gov | Last Updated 2021-06-30T15:21:29.000Z
The data here is from the report entitled Trends in Enrollment, Credit Attainment, and Remediation at Connecticut Public Universities and Community Colleges: Results from P20WIN for the High School Graduating Classes of 2010 through 2016. The report answers three questions: 1. Enrollment: What percentage of the graduating class enrolled in a Connecticut public university or community college (UCONN, the four Connecticut State Universities, and 12 Connecticut community colleges) within 16 months of graduation? 2. Credit Attainment: What percentage of those who enrolled in a Connecticut public university or community college within 16 months of graduation earned at least one year’s worth of credits (24 or more) within two years of enrollment? 3. Remediation: What percentage of those who enrolled in one of the four Connecticut State Universities or one of the 12 community colleges within 16 months of graduation took a remedial course within two years of enrollment? Notes on the data: CT Remed: % Enrolled in Remediation is a subset of the % Enrolled in 16 Months.
- API data.cambridgema.gov | Last Updated 2022-08-01T04:04:47.000Z
View full metadata https://www.cambridgema.gov/GIS/gisdatadictionary/CDD/CDD_LandUse Description This data set derives from several sources. The primary source is a data dump from the VISION assessing data system, which provided data up to date as of January 1, 2012, and is supplemented by information from subsequent building permits and Development Logs. (Use codes provided by this system combine aspects of land use, tax status, and condominium status. In an effort to clarify land use type the data has been cleaned and subdivided to break the original use code into several different fields.) The data set has further been supplemented and updated with development information provided by building permits issued by the Inspectional Services Department and from data found in the Development Log publication. Information from these sources is added to the data set periodically. Land use status is up to date as of the Last Modified date. Differences From “Official” Parcel Layer The Cambridge GIS system maintains a separate layer of land parcels reflecting up to date subdivision and ownership. The parcel data associated with the Land Use Data set differs from the “official” parcel layer in a number of cases. For that reason this separate parcel layer is provided to work with land use data in a GIS environment. See the Assessing Department’s Parcel layer for the most up-to-date land parcel boundaries. About Edit Dates This data is automatically updated on a set schedule. The Socrata edit date may not reflect the actual edit dates in the data. For more details please see the update date on the full metadata page or view the edit date within the data rows.
- API data.austintexas.gov | Last Updated 2021-04-14T22:07:33.000Z
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.
Baseline Survey for an Impact Evaluation of the Greenbelt Transformation Initiative in South Sudan-Data: Section 1data.usaid.gov | Last Updated 2018-11-12T06:12:32.000Z
This dataset is derived from a 2013 household baseline survey in the country's Greenbelt region as part of an impact evaluation of the Food, Agribusiness, and Rural Markets (FARM) Project, which is intended to improve agricultural sector productivity and marketing in the Greenbelt and to support increasing South Sudan's food supply to reach food self-sufficiency. In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully.