This dataset provides population 25 years and over estimates by sex and educational attainment for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B15002.

Sex includes Male, Female and Both.

Educational Attainment includes the following: No School; PK to 4th Grade; 5th to 6th Grade; 7th to 8th Grade; 9th Grade; 10th Grade; 11th Grade; 12th Grade, No Diploma; High School Diploma or Equivalent; Some College, Less than Year; Some College, One Year or More; Associates Degree; Bachelors Degree; Masters Degree; Professional Degree; and Doctorate Degree.

Each have been placed in the following educational categories: Less than High School, High School Graduate; Some College or Associates Degree; and Bachelors Degree or Higher.

The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.

This dataset provides population 25 years and over estimates by educational attainment for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B15003. Levels of educational attainment include the following: No schooling completed; Nursery school; Kindergarten; 1st grade; 2nd grade; 3rd grade; 4th grade; 5th grade; 6th grade; 7th grade; 8th grade; 9th grade; 10th grade; 11th grade; 12th grade, no diploma; Regular high school diploma; GED or alternative credential; Some college, less than 1 year; Some college, 1 or more years, no degree; Associate's degree; Bachelor's degree; Master's degree; Professional school degree; and Doctorate degree.

The survey on the professional integration of graduates is part of the system of surveys on the transition from education to employment. As its primary objective, these surveys want to detect the employment status of young people in a predetermined distance from an educational qualification (respectively, diploma, degree, doctorate). The choice to analyze the phenomenon at a certain distance from the qualification, traditionally detected in "three years", is motivated both by the need to take account of the conclusion of further qualification activities and by the fact that the time of insertion in the labour market is not short, especially if you also want to investigate the quality of their job. Unlike previous rounds, the 2011 survey on the professional integration of graduates, now in its eighth edition, was conducted at a greater distance from degree (four years) and for the first time it has investigated on the employment outcomes of graduates in 2007 biennial specialized courses (the "+2" introduced with the reform of the academic cycles in Italy). In fact, the greatest distance from graduation has allowed us to follow, longitudinally, graduate people in "three-year" courses in 2007 (Bachelor's degree) to the possible consecutive specialist degree, obtaining early feedback on how many workers also have obtained a specialist degree since 2007. This edition of the survey includes: - graduates in "three-year" courses (Bachelor's degree); - graduates in "single-cycle" courses (which includes, in addition to specialist degrees/single-cycle degrees, the 4-6 years "traditional" degrees); - graduates in specialist degree/master (two-year duration). The survey questionnaire is divided into five sections. the first section, which covers all respondents, deals with the information on studying/training activities carried out from the high school diploma to the time of the interview, with particular attention to the degree program concluded in 2007: any other academic degrees before graduating in 2007; reasons for the choice of the University; possible recognition of course credits; course attendance; satisfaction with their choices of study; etc.. The second section is devoted to work and it is only addressed to people claiming to perform a work activity. Among others, these pieces of information are asked: employment, sector of economic activity, employment status, type of contract, occupation, work schedule, earnings, current job satisfaction. In particular, with reference to the earnings, for the first time in the 2011 edition of the survey, different questions were adopted depending on whether the respondent was a self-employed person (in this case it was asked for annual net salary) or an employee or a project worker (in these cases it was asked for the monthly net salary). The third section is devoted to the job search, and it is only addressed to respondents that they were looking for job. these pieces of information are asked: the last action regarding the job search; the preferred type of work and schedule; the propensity to moving from your country/city; etc... The fourth section deals with mobility, and it is designed to collect information on: residence prior to enrollment at the university; any transfers for study purposes; place where he usually lives at the time of the interview and motivations, etc.. Finally, the last section of the questionnaire is addressed to all respondents, collecting information on: parents' education level and job; interviewee's marital status, children (if any) and living situation (whom s/he lives with) of the interviewee.

Our Demographics package in the USA offers data pertaining to the education of residents of the United States of America at Census Block Level. Each data variable is available as a sum, or as a percentage of the total population within each selected area.

What is included?

At the Census Block level, this dataset includes some of the following key features:

Highest Educational Attainment

• High-school Diploma
• College - No Degree
• GED
• Associates Degree
• Bachelor's Degree
• Master's Degree
• Doctorate Degree
• Professional School Degree

Schooling In Child Population

• No Schooling
• Nursery School
• Kindergarten
• Primary School

Bachelor's Degree Attained

• Arts/Humanities/Other
• Business
• Education
• Science/Engineering

• • Highest Educational Attainment: Marketers can use this data to tailor their campaigns based on the level of education achieved by their target audience. For instance, educational institutions may focus on promoting advanced degree programs to individuals with a bachelor's degree or higher, while brands offering products related to skill development might target those with a high-school diploma or college degree.
  • Schooling In Child Population: This data provides insights into the educational stages of the child population, allowing marketers to customize their strategies. For example, companies specializing in children's products can create targeted promotions for specific age groups, such as educational toys for those in nursery or kindergarten.
  • Bachelor's Degree Attained: Marketers can leverage this information to tailor campaigns based on the specific field of study for individuals with a bachelor's degree. For instance, businesses offering services aligned with certain disciplines, like technology or the arts, can refine their messaging to appeal to the interests and preferences associated with each academic field.

• This demographic data is typically available at the census block level. These blocks are smaller, more detailed units designed for statistical purposes, enabling a more precise analysis of population, housing, and demographic data. Census blocks may vary in size and shape but are generally more localized compared to ZIP codes.

  Still looking for demographic data at the postal code level? Contact sales.

• There are numerous other census data datasets available for the United States, covering a wide range of demographics. These include information on:

  • Commuting
  • Educational Attainment
  • Employment
  • Families
  • Finance
  • Housing

Analysis of ‘International Educational Attainment by Year & Age’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/international-comp-attainmente on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

The National Center for Education Statistics (NCES) is the primary federal entity for collecting and analyzing data related to education in the U.S. and other nations. NCES is located within the U.S. Department of Education and the Institute of Education Sciences. NCES fulfills a Congressional mandate to collect, collate, analyze, and report complete statistics on the condition of American education; conduct and publish reports; and review and report on education activities internationally.

• Table 603.10. Percentage of the population 25 to 64 years old who completed high school, by age group and country: Selected years, 2001 through 2012
• Table 603.20. Percentage of the population 25 to 64 years old who attained selected levels of postsecondary education, by age group and country: 2001 and 2012
• Table 603.30. Percentage of the population 25 to 64 years old who attained a bachelor's or higher degree, by age group and country: Selected years, 1999 through 2012
• Table 603.40 Percentage of the population 25 to 64 years old who attained a postsecondary vocational degree, by age group and country: Selected years, 1999 through 2012
• Table 603.50 Number of bachelor's degree recipients per 100 persons at the typical minimum age of graduation, by sex and country: Selected years, 2005 through 2012
• Table 603.60. Percentage of postsecondary degrees awarded to women, by field of study and country: 2013
• Table 603.70. Percentage of bachelor's or equivalent degrees awarded in mathematics, science, and engineering, by field of study and country: 2013
• Table 603.80. Percentage of master's or equivalent degrees and of doctoral or equivalent degrees awarded in mathematics, science, and engineering, by field of study and country: 2013
• Table 603.90. Employment to population ratios of -25 to 64-year-olds, by sex, highest level of educational attainment, and country: 2014

Source: https://nces.ed.gov/programs/digest/current_tables.asp

This dataset was created by National Center for Education Statistics and contains around 100 samples along with Unnamed: 20, Unnamed: 24, technical information and other features such as: - Unnamed: 11 - Unnamed: 16 - and more.

How to use this dataset

• Analyze Unnamed: 15 in relation to Unnamed: 6
• Study the influence of Unnamed: 1 on Unnamed: 10
• More datasets

Acknowledgements

If you use this dataset in your research, please credit National Center for Education Statistics

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--- Original source retains full ownership of the source dataset ---

High school graduate (includes equivalency) Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in United States by age, education, race, gender, work experience and more.

Less than high school graduate Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in United States by age, education, race, gender, work experience and more.

**************** NTU Pedestrian Dataset *******************Attached files contain our data collected inside Nanyang Technological University Campus for pedestrian intention prediction. The dataset is particularly designed to capture spontaneous vehicle influences on pedestrian crossing/not-crossing intention.We utilize this dataset in our journal paper "Context Model for Pedestrian Intention Prediction using Factored Latent-Dynamic Conditional Random Fields" accepted by IEEE Transactions on Intelligent Transportation Systems.The dataset consists of 35 crossing and 35 stopping* (not-crossing) scenarios. The image sequences are in 'Image_sequences' folder.'stopping_instants.csv' and 'crossing_instants.csv' files provide the stopping and crossing instants respectively, utilized for labeling the data and providing ground-truth for evaluation. Camera1 and Camera2 images are synchronized. Two cameras were used to capture the whole scene of interest.We provide pedestrian and vehicle bounding boxes obtained from [1]. The occlusions and mis-detections are linearly interpolated. All necessary detections are stored in 'Object_detector_pedestrians_vehicles' folder. Each column within the csv files ('car_bndbox_..') corresponds to a unique tracked car within each image sequence. Each of the pedestrian csv files ('ped_bndbox_..') contains only one column, as we consider each pedestrian in the scene separately.Additional details:* [xmin xmax ymin ymax] = left right top down* Dataset frequency: 15 fps.* Camera parameters (in pixels): f = 1135, principal point = (960, 540).Additionally, we provide semantic segmentation output [2] and our depth parameters. As the data were collected in two phases, there are two files in each folder, highlighting the sequences in each phase.Crossing sequences 1-28 and stopping sequences 1-24 were collected in Phase 1, while crossing sequences 29-35 and stopping sequences 25-35 were collected in Phase 2.We obtained the optical flow from [3]. Our model (FLDCRF) codes are available here: https://github.com/satyajitneogiju/FLDCRF-for-sequence-labelingIf you use our dataset in your research, please cite our paper(s):1. S. Neogi, M. Hoy, K. Dang, H. Yu, J. Dauwels, "Context Model for Pedestrian Intention Prediction using Factored Latent-Dynamic Conditional Random Fields". Accepted by IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2019.2. "S. Neogi, M. Hoy, W. Chaoqun, J. Dauwels, 'Context Based Pedestrian Intention Prediction Using Factored Latent Dynamic Conditional Random Fields', IEEE SSCI-2017."Please email us if you have any questions:1. Satyajit Neogi, PhD Student, Nanyang Technological University @ satyajit001@e.ntu.edu.sg2. Justin Dauwels, Associate Professor, Nanyang Technological University @ jdauwels@ntu.edu.sgOur other group members include:3. Dr. Michael Hoy, @ mch.hoy@gmail.com4. Dr. Kang Dang, @ kangdang@gmail.com5. Ms. Lakshmi Prasanna Kachireddy,6. Mr. Mok Bo Chuan Lance, and7. Mr. Xu Yan References:1. S. Ren, K. He, R. Girshick, J. Sun, Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", NIPS 2015.2. A. Kendall, V. Badrinarayanan, R. Cipolla,Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding", BMVC 2017.3. C. Liu. ``Beyond Pixels: Exploring New Representations and Applications for Motion Analysis". Doctoral Thesis. Massachusetts Institute of Technology. May 2009.* Please note, we had to remove sequence Stopping-33 for privacy reasons.FUNDINGSTE-NTU NRF corporate lab@university scheme

U.S. citizens with a professional degree had the highest median household income in 2023, at 172,100 U.S. dollars. In comparison, those with less than a 9th grade education made significantly less money, at 35,690 U.S. dollars. Household income The median household income in the United States has fluctuated since 1990, but rose to around 70,000 U.S. dollars in 2021. Maryland had the highest median household income in the United States in 2021. Maryland’s high levels of wealth is due to several reasons, and includes the state's proximity to the nation's capital. Household income and ethnicity The median income of white non-Hispanic households in the United States had been on the rise since 1990, but declining since 2019. While income has also been on the rise, the median income of Hispanic households was much lower than those of white, non-Hispanic private households. However, the median income of Black households is even lower than Hispanic households. Income inequality is a problem without an easy solution in the United States, especially since ethnicity is a contributing factor. Systemic racism contributes to the non-White population suffering from income inequality, which causes the opportunity for growth to stagnate.

With the enactment of the Higher Education Opportunity Act (HEOA) of 2008, five Predominantly Black Institutions are eligible to receive funding to improve graduate education opportunities at the master’s level in mathematics, engineering, physical or natural sciences, computer science, information technology, nursing, allied health or other scientific disciplines where African American students are underrepresented. Types of Projects Institutions may use federal funds for activities that include: Purchase, rental or lease of scientific or laboratory equipment for educational purposes, including instructional and research purposes; Construction, maintenance, renovation and improvement in classroom, library, laboratory and other instructional facilities, including purchase or rental of telecommunications technology equipment or services; Purchase of library books, periodicals, technical and other scientific journals, microfilm, microfiche, and other educational materials, including telecommunications program materials; Scholarships, fellowships, and other financial assistance for needy graduate students to permit the enrollment of students in, and completion of a master’s degree in mathematics, engineering, physical or natural sciences, computer science, information technology, nursing, allied health, or other scientific disciplines in which African Americans are underrepresented; Establishing or improving a development office to strengthen and increase contributions from alumni and the private sector; Assisting in the establishment or maintenance of an institutional endowment to facilitate financial independence pursuant to Section 331; Funds and administrative management, and the acquisition of equipment, including software, for use in strengthening funds management and management information systems; Acquisition of real property that is adjacent to the campus in connection with the construction, renovation, or improvement of, or an addition to, campus facilities; Education or financial information designed to improve the financial literacy and economic literacy of students or the students’ families, especially with regards to student indebtedness and student assistance programs under title IV; Tutoring, counseling, and student service programs designed to improve academic success; Faculty professional development, faculty exchanges, and faculty participation in professional conferences and meetings; and Other activities proposed in the application that are approved by the Secretary as part of the review and acceptance of such application.

United States US: Labour Force With Advanced Education: Female: % of Female Working-age Population data was reported at 77.809 % in 2017. This records a decrease from the previous number of 78.336 % for 2016. United States US: Labour Force With Advanced Education: Female: % of Female Working-age Population data is updated yearly, averaging 82.936 % from Dec 1994 (Median) to 2017, with 24 observations. The data reached an all-time high of 86.467 % in 1994 and a record low of 77.809 % in 2017. United States US: Labour Force With Advanced Education: Female: % of Female Working-age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Labour Force. The percentage of the working age population with an advanced level of education who are in the labor force. Advanced education comprises short-cycle tertiary education, a bachelor’s degree or equivalent education level, a master’s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average;

High school graduate (includes equivalency) Health Insurance Coverage Statistics for 2023. This is part of a larger dataset covering consumer health insurance coverage rates in United States by age, education, race, gender, work experience and more.

Less than high school graduate Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in American Fork, Utah by age, education, race, gender, work experience and more.

In 2023, the mean income of women with a doctorate degree in the United States stood at 139,100 U.S. dollars. For men with the same degree, mean earnings stood at 175,500 U.S. dollars. On average in 2023, American men earned 91,590 U.S. dollars, while American women earned 65,987 U.S. dollars.