65 datasets found
  1. US Highschool students dataset

    • kaggle.com
    zip
    Updated Apr 14, 2024
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    peter mushemi (2024). US Highschool students dataset [Dataset]. https://www.kaggle.com/datasets/petermushemi/us-highschool-students-dataset
    Explore at:
    zip(0 bytes)Available download formats
    Dataset updated
    Apr 14, 2024
    Authors
    peter mushemi
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The dataset is related to student data, from an educational research study focusing on student demographics, academic performance, and related factors. Here’s a general description of what each column likely represents:

    Sex: The gender of the student (e.g., Male, Female). Age: The age of the student. Name: The name of the student. State: The state where the student resides or where the educational institution is located. Address: Indicates whether the student lives in an urban or rural area. Famsize: Family size category (e.g., LE3 for families with less than or equal to 3 members, GT3 for more than 3). Pstatus: Parental cohabitation status (e.g., 'T' for living together, 'A' for living apart). Medu: Mother's education level (e.g., Graduate, College). Fedu: Father's education level (similar categories to Medu). Mjob: Mother's job type. Fjob: Father's job type. Guardian: The primary guardian of the student. Math_Score: Score obtained by the student in Mathematics. Reading_Score: Score obtained by the student in Reading. Writing_Score: Score obtained by the student in Writing. Attendance_Rate: The percentage rate of the student’s attendance. Suspensions: Number of times the student has been suspended. Expulsions: Number of times the student has been expelled. Teacher_Support: Level of support the student receives from teachers (e.g., Low, Medium, High). Counseling: Indicates whether the student receives counseling services (Yes or No). Social_Worker_Visits: Number of times a social worker has visited the student. Parental_Involvement: The level of parental involvement in the student's academic life (e.g., Low, Medium, High). GPA: The student’s Grade Point Average, a standard measure of academic achievement in schools.

    This dataset provides a comprehensive look at various factors that might influence a student's educational outcomes, including demographic factors, academic performance metrics, and support structures both at home and within the educational system. It can be used for statistical analysis to understand and improve student success rates, or for targeted interventions based on specific identified needs.

  2. N

    College Springs, IA Population Breakdown by Gender Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). College Springs, IA Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b2297cea-f25d-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    College Springs
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of College Springs by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of College Springs across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a majority of male population, with 56.68% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the College Springs is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of College Springs total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for College Springs Population by Race & Ethnicity. You can refer the same here

  3. N

    University Heights, OH Population Breakdown by Gender Dataset: Male and...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). University Heights, OH Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b25914fb-f25d-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    University Heights, Ohio
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of University Heights by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of University Heights across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a slight majority of female population, with 51.06% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the University Heights is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of University Heights total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for University Heights Population by Race & Ethnicity. You can refer the same here

  4. SPD24 - Student Performance Data revised Features

    • kaggle.com
    Updated Aug 1, 2024
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    DatasetEngineer (2024). SPD24 - Student Performance Data revised Features [Dataset]. http://doi.org/10.34740/kaggle/dsv/9083250
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 1, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    DatasetEngineer
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Student Performance Dataset 2024 Overview This dataset comprises detailed information about high school students in China, collected from various universities and schools. It is designed to analyze the factors influencing student performance, well-being, and engagement. The data includes a wide range of features such as demographic details, academic performance, health status, parental support, and more. The participating institutions include prominent universities such as Tsinghua University, Peking University, Fudan University, Shanghai Jiao Tong University, and Zhejiang University.

    Dataset Description Features Student ID: Unique identifier for each student. Gender: Gender of the student (Male/Female). Age: Age of the student. Grade Level: The grade level of the student (e.g., 9, 10, 11, 12). Attendance Rate: The percentage of days the student attended school. Study Hours: Average number of hours the student spends studying daily. Parental Education Level: The highest level of education attained by the student's parents. Parental Involvement: The level of parental involvement in the student's education (High, Medium, Low). Extracurricular Activities: Whether the student participates in extracurricular activities (Yes/No). Socioeconomic Status: Socioeconomic status of the student's family (High, Medium, Low). Previous Academic Performance: Previous academic performance level (High, Medium, Low). Class Participation: The level of participation in class (High, Medium, Low). Health Status: General health status of the student (Good, Average, Poor). Access to Learning Resources: Whether the student has access to necessary learning resources (Yes/No). Internet Access: Whether the student has access to the internet (Yes/No). Learning Style: Preferred learning style of the student (Visual, Auditory, Kinesthetic). Teacher-Student Relationship: Quality of the relationship between the student and teachers (Positive, Neutral, Negative). Peer Influence: Influence of peers on the student's behavior and performance (Positive, Neutral, Negative). Motivation Level: Student's level of motivation (High, Medium, Low). Hours of Sleep: Average number of hours the student sleeps per night. Diet Quality: Quality of the student's diet (Good, Average, Poor). Transportation Mode: Mode of transportation used by the student to commute to school (Bus, Car, Walk, Bike). School Type: Type of school attended by the student (Public, Private). School Location: Location of the school (Urban, Rural). Homework Completion Rate: The rate at which the student completes homework assignments. Reading Proficiency: Proficiency level in reading. Math Proficiency: Proficiency level in mathematics. Science Proficiency: Proficiency level in science. Language Proficiency: Proficiency level in language. Physical Activity Level: The level of physical activity (High, Medium, Low). Screen Time: Average daily screen time in hours. Bullying Incidents: Number of bullying incidents the student has experienced. Special Education Services: Whether the student receives special education services (Yes/No). Counseling Services: Whether the student receives counseling services (Yes/No). Learning Disabilities: Whether the student has any learning disabilities (Yes/No). Behavioral Issues: Whether the student has any behavioral issues (Yes/No). Attendance of Tutoring Sessions: Whether the student attends tutoring sessions (Yes/No). School Climate: Overall perception of the school's environment (Positive, Neutral, Negative). Parental Employment Status: Employment status of the student's parents (Employed, Unemployed). Household Size: Number of people living in the student's household. Performance Score: Overall performance score of the student (Low, Medium, High).

  5. Student Performance Factors

    • kaggle.com
    Updated Nov 26, 2024
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    Practice Data Analysis With Me (2024). Student Performance Factors [Dataset]. https://www.kaggle.com/datasets/lainguyn123/student-performance-factors
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 26, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Practice Data Analysis With Me
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Description

    This dataset provides a comprehensive overview of various factors affecting student performance in exams. It includes information on study habits, attendance, parental involvement, and other aspects influencing academic success.

    Column Descriptions

    AttributeDescription
    Hours_StudiedNumber of hours spent studying per week.
    AttendancePercentage of classes attended.
    Parental_InvolvementLevel of parental involvement in the student's education (Low, Medium, High).
    Access_to_ResourcesAvailability of educational resources (Low, Medium, High).
    Extracurricular_ActivitiesParticipation in extracurricular activities (Yes, No).
    Sleep_HoursAverage number of hours of sleep per night.
    Previous_ScoresScores from previous exams.
    Motivation_LevelStudent's level of motivation (Low, Medium, High).
    Internet_AccessAvailability of internet access (Yes, No).
    Tutoring_SessionsNumber of tutoring sessions attended per month.
    Family_IncomeFamily income level (Low, Medium, High).
    Teacher_QualityQuality of the teachers (Low, Medium, High).
    School_TypeType of school attended (Public, Private).
    Peer_InfluenceInfluence of peers on academic performance (Positive, Neutral, Negative).
    Physical_ActivityAverage number of hours of physical activity per week.
    Learning_DisabilitiesPresence of learning disabilities (Yes, No).
    Parental_Education_LevelHighest education level of parents (High School, College, Postgraduate).
    Distance_from_HomeDistance from home to school (Near, Moderate, Far).
    GenderGender of the student (Male, Female).
    Exam_ScoreFinal exam score.
  6. N

    University Place, WA Population Breakdown by Gender Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). University Place, WA Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b2591762-f25d-11ef-8c1b-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    University Place, Washington
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of University Place by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of University Place across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a slight majority of female population, with 51.99% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the University Place is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of University Place total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for University Place Population by Race & Ethnicity. You can refer the same here

  7. N

    University Park, MD Population Breakdown by Gender Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). University Park, MD Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b259166b-f25d-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    University Park, Maryland
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of University Park by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of University Park across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a slight majority of female population, with 50.04% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the University Park is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of University Park total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for University Park Population by Race & Ethnicity. You can refer the same here

  8. Data from: Understanding Crime Victimization Among College Students in the...

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Understanding Crime Victimization Among College Students in the United States, 1993-1994 [Dataset]. https://catalog.data.gov/dataset/understanding-crime-victimization-among-college-students-in-the-united-states-1993-1994-8afc5
    Explore at:
    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    United States
    Description

    This study was designed to collect college student victimization data to satisfy four primary objectives: (1) to determine the prevalence and nature of campus crime, (2) to help the campus community more fully assess crime, perceived risk, fear of victimization, and security problems, (3) to aid in the development and evaluation of location-specific and campus-wide security policies and crime prevention measures, and (4) to make a contribution to the theoretical study of campus crime and security. Data for Part 1, Student-Level Data, and Part 2, Incident-Level Data, were collected from a random sample of college students in the United States using a structured telephone interview modeled after the redesigned National Crime Victimization Survey administered by the Bureau of Justice Statistics. Using stratified random sampling, over 3,000 college students from 12 schools were interviewed. Researchers collected detailed information about the incident and the victimization, and demographic characteristics of victims and nonvictims, as well as data on self-protection, fear of crime, perceptions of crime on campus, and campus security measures. For Part 3, School Data, the researchers surveyed campus officials at the sampled schools and gathered official data to supplement institution-level crime prevention information obtained from the students. Mail-back surveys were sent to directors of campus security or campus police at the 12 sampled schools, addressing various aspects of campus security, crime prevention programs, and crime prevention services available on the campuses. Additionally, mail-back surveys were sent to directors of campus planning, facilities management, or related offices at the same 12 schools to obtain information on the extent and type of planning and design actions taken by the campus for crime prevention. Part 3 also contains data on the characteristics of the 12 schools obtained from PETERSON'S GUIDE TO FOUR-YEAR COLLEGES (1994). Part 4, Census Data, is comprised of 1990 Census data describing the census tracts in which the 12 schools were located and all tracts adjacent to the schools. Demographic variables in Part 1 include year of birth, sex, race, marital status, current enrollment status, employment status, residency status, and parents' education. Victimization variables include whether the student had ever been a victim of theft, burglary, robbery, motor vehicle theft, assault, sexual assault, vandalism, or harassment. Students who had been victimized were also asked the number of times victimization incidents occurred, how often the police were called, and if they knew the perpetrator. All students were asked about measures of self-protection, fear of crime, perceptions of crime on campus, and campus security measures. For Part 2, questions were asked about the location of each incident, whether the offender had a weapon, a description of the offense and the victim's response, injuries incurred, characteristics of the offender, and whether the incident was reported to the police. For Part 3, respondents were asked about how general campus security needs were met, the nature and extent of crime prevention programs and services available at the school (including when the program or service was first implemented), and recent crime prevention activities. Campus planners were asked if specific types of campus security features (e.g., emergency telephone, territorial markers, perimeter barriers, key-card access, surveillance cameras, crime safety audits, design review for safety features, trimming shrubs and underbrush to reduce hiding places, etc.) were present during the 1993-1994 academic year and if yes, how many or how often. Additionally, data were collected on total full-time enrollment, type of institution, percent of undergraduate female students enrolled, percent of African-American students enrolled, acreage, total fraternities, total sororities, crime rate of city/county where the school was located, and the school's Carnegie classification. For Part 4, Census data were compiled on percent unemployed, percent having a high school degree or higher, percent of all persons below the poverty level, and percent of the population that was Black.

  9. p

    Young Women's College Prep Academy

    • publicschoolreview.com
    json, xml
    Updated Nov 13, 2022
    + more versions
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    Public School Review (2022). Young Women's College Prep Academy [Dataset]. https://www.publicschoolreview.com/young-women-s-college-prep-academy-profile
    Explore at:
    xml, jsonAvailable download formats
    Dataset updated
    Nov 13, 2022
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Dec 31, 2025
    Description

    Historical Dataset of Young Women's College Prep Academy is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2013-2023),Total Classroom Teachers Trends Over Years (2013-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2013-2023),Asian Student Percentage Comparison Over Years (2013-2023),Hispanic Student Percentage Comparison Over Years (2013-2023),Black Student Percentage Comparison Over Years (2013-2023),White Student Percentage Comparison Over Years (2013-2023),Two or More Races Student Percentage Comparison Over Years (2012-2023),Diversity Score Comparison Over Years (2013-2023),Free Lunch Eligibility Comparison Over Years (2013-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2012-2023),Reading and Language Arts Proficiency Comparison Over Years (2012-2022),Math Proficiency Comparison Over Years (2012-2023),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2012-2023),Graduation Rate Comparison Over Years (2017-2023)

  10. College enrollment in public and private institutions in the U.S. 1965-2031

    • statista.com
    • thefarmdosupply.com
    Updated Mar 25, 2025
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    Statista (2025). College enrollment in public and private institutions in the U.S. 1965-2031 [Dataset]. https://www.statista.com/statistics/183995/us-college-enrollment-and-projections-in-public-and-private-institutions/
    Explore at:
    Dataset updated
    Mar 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    There were approximately 18.58 million college students in the U.S. in 2022, with around 13.49 million enrolled in public colleges and a further 5.09 million students enrolled in private colleges. The figures are projected to remain relatively constant over the next few years.

    What is the most expensive college in the U.S.? The overall number of higher education institutions in the U.S. totals around 4,000, and California is the state with the most. One important factor that students – and their parents – must consider before choosing a college is cost. With annual expenses totaling almost 78,000 U.S. dollars, Harvey Mudd College in California was the most expensive college for the 2021-2022 academic year. There are three major costs of college: tuition, room, and board. The difference in on-campus and off-campus accommodation costs is often negligible, but they can change greatly depending on the college town.

    The differences between public and private colleges Public colleges, also called state colleges, are mostly funded by state governments. Private colleges, on the other hand, are not funded by the government but by private donors and endowments. Typically, private institutions are  much more expensive. Public colleges tend to offer different tuition fees for students based on whether they live in-state or out-of-state, while private colleges have the same tuition cost for every student.

  11. w

    AGE Percent Females by 5 Yr Age Groups NMSD 2000

    • data.wu.ac.at
    • gstore.unm.edu
    • +2more
    csv, excel, geojson +9
    Updated Jun 25, 2014
    + more versions
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    Earth Data Analysis Center, University of New Mexico (2014). AGE Percent Females by 5 Yr Age Groups NMSD 2000 [Dataset]. https://data.wu.ac.at/odso/data_gov/MDlmODMzNWMtMjYxNy00NmVmLWE1OTYtMmY0MTkxNTZmYjEz
    Explore at:
    shp, csv, wfs, kml, gml, xml, geojson, html, excel, json, wms, zipAvailable download formats
    Dataset updated
    Jun 25, 2014
    Dataset provided by
    Earth Data Analysis Center, University of New Mexico
    Area covered
    cbfe9553ac5b28b6dd38dbe2a649cbf667641835
    Description

    The 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on the latest available governmental unit boundaries. The Census TIGER database represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The 2006 Second Edition TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries.

    This shapefile represents the current State Senate Districts for New Mexico as posted on the Census Bureau website for 2006.

  12. p

    Trends in Two or More Races Student Percentage (2021-2023): City University...

    • publicschoolreview.com
    Updated Sep 16, 2018
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    Public School Review (2018). Trends in Two or More Races Student Percentage (2021-2023): City University School Girls Preparatory vs. Tennessee vs. Memphis-Shelby County Schools [Dataset]. https://www.publicschoolreview.com/city-university-school-girls-preparatory-profile
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    Dataset updated
    Sep 16, 2018
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Shelby County Schools
    Description

    This dataset tracks annual two or more races student percentage from 2021 to 2023 for City University School Girls Preparatory vs. Tennessee and Memphis-Shelby County Schools

  13. N

    University City, MO Population Breakdown by Gender Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
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    Neilsberg Research (2025). University City, MO Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b2591404-f25d-11ef-8c1b-3860777c1fe6/
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    json, csvAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    University City, Missouri
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of University City by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of University City across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a majority of female population, with 54.68% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the University City is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of University City total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for University City Population by Race & Ethnicity. You can refer the same here

  14. d

    Percentage of Women Who Have Received Preventative Services (LGHC Indicator)...

    • catalog.data.gov
    • data.ca.gov
    • +4more
    Updated Jul 23, 2025
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    California Department of Public Health (2025). Percentage of Women Who Have Received Preventative Services (LGHC Indicator) [Dataset]. https://catalog.data.gov/dataset/percentage-of-women-who-have-received-preventative-services-lghc-indicator-cf724
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    Dataset updated
    Jul 23, 2025
    Dataset provided by
    California Department of Public Health
    Description

    This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. This table displays the percentage of women ages 18-44 who have received preventative services. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by the Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. The column percentages are weighted to the 2010 California Department of Finance (DOF) population statistics. Population estimates were obtained from the CA DOF for age, race/ethnicity, and sex. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

  15. p

    City University School Girls Preparatory

    • publicschoolreview.com
    json, xml
    Updated Sep 16, 2018
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    Public School Review (2018). City University School Girls Preparatory [Dataset]. https://www.publicschoolreview.com/city-university-school-girls-preparatory-profile
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    xml, jsonAvailable download formats
    Dataset updated
    Sep 16, 2018
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2014 - Dec 31, 2025
    Description

    Historical Dataset of City University School Girls Preparatory is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2014-2023),Total Classroom Teachers Trends Over Years (2014-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2014-2023),Hispanic Student Percentage Comparison Over Years (2015-2022),Black Student Percentage Comparison Over Years (2014-2023),Two or More Races Student Percentage Comparison Over Years (2021-2023),Diversity Score Comparison Over Years (2015-2023),Free Lunch Eligibility Comparison Over Years (2014-2023),Reading and Language Arts Proficiency Comparison Over Years (2014-2022),Math Proficiency Comparison Over Years (2014-2023),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2014-2023)

  16. World University Rankings 2021

    • kaggle.com
    Updated Nov 25, 2020
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    Matheus Gratz (2020). World University Rankings 2021 [Dataset]. https://www.kaggle.com/matheusgratz/world-university-rankings-2021/activity
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 25, 2020
    Dataset provided by
    Kaggle
    Authors
    Matheus Gratz
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    World University Rankings - 2021

    Source: www.timeshighereducation.com

    Pages (HTML FILES): * Rankings

    Files: * Rankings (universities_ranking.csv/JSON) - Contains all the information from the Rankings page * Scores (universities_scores.csv/JSON) - Contains more detailed scores from the Scores page

    Information Collected

    Key statistics/Rankings The data shown under key statistics are those provided by the university itself in its submission to the Times Higher Education World University Rankings. It represents data from the 2019/20 academic year, and may vary from subsequent or earlier years.

    • Ranking
    • Name/Title
    • Country/Region
    • No. of FTE Students This is the number of full-time equivalent students at the university.
    • No. of Students per Staff This is the ratio of full-time equivalent students to the number of academic staff – those involved in teaching or research.
    • % International Students The percentage of students originating from outside the country of the university.
    • Female:Male Ratio The ratio of female to male students at the university.

    Scores: * Ranking * Name/Title * Country/Region * Overall * Teaching * Research * Citators * Industry Income * International Outlook

  17. Postsecondary graduates, by province of study and level of study

    • www150.statcan.gc.ca
    • datasets.ai
    • +2more
    Updated Mar 22, 2024
    + more versions
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    Government of Canada, Statistics Canada (2024). Postsecondary graduates, by province of study and level of study [Dataset]. http://doi.org/10.25318/3710003001-eng
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    Dataset updated
    Mar 22, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Statistics on postsecondary graduates, including the number of graduates, the percentage of female graduates and age at graduation, are presented by the province of study and the level of study. Estimates are available at five-year intervals.

  18. p

    Trends in White Student Percentage (2013-2023): Young Women's College Prep...

    • publicschoolreview.com
    Updated Nov 13, 2022
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    Public School Review (2022). Trends in White Student Percentage (2013-2023): Young Women's College Prep Academy vs. Texas vs. Houston Independent School District [Dataset]. https://www.publicschoolreview.com/young-women-s-college-prep-academy-profile
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    Dataset updated
    Nov 13, 2022
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Houston Independent School District, Houston, Texas
    Description

    This dataset tracks annual white student percentage from 2013 to 2023 for Young Women's College Prep Academy vs. Texas and Houston Independent School District

  19. p

    Trends in Black Student Percentage (2013-2023): Young Women's College Prep...

    • publicschoolreview.com
    Updated Nov 13, 2022
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    Public School Review (2022). Trends in Black Student Percentage (2013-2023): Young Women's College Prep Academy vs. Texas vs. Houston Independent School District [Dataset]. https://www.publicschoolreview.com/young-women-s-college-prep-academy-profile
    Explore at:
    Dataset updated
    Nov 13, 2022
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Houston Independent School District, Houston, Texas
    Description

    This dataset tracks annual black student percentage from 2013 to 2023 for Young Women's College Prep Academy vs. Texas and Houston Independent School District

  20. f

    Effects of COVID-19 Restrictions on University Students Mental Health

    • figshare.com
    pdf
    Updated Nov 17, 2021
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    Collateral Global (2021). Effects of COVID-19 Restrictions on University Students Mental Health [Dataset]. http://doi.org/10.6084/m9.figshare.16885330.v2
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    pdfAvailable download formats
    Dataset updated
    Nov 17, 2021
    Dataset provided by
    figshare
    Authors
    Collateral Global
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Restrictions affecting mental health and wellbeing can significantly affect vulnerable populations that include university students. Therefore, we undertook a scoping review by searching LitCovid, the WHO Covid-19 database, Google Scholar and bibliographies of retrieved articles for systematic reviews that included data on depression and anxiety in university students during the COVID-19 pandemic. We found nine systematic reviews (two were preprints) that varied from five included studies to 89. The quality of the short-term evidence was rated low to moderate, and evidence for the medium to long term impact was low (the prevalence estimates may change substantially if further high-quality evidence becomes available).Reviews consistently reported high prevalence rates of anxiety and depression amongst university and college students. Rates of depression and anxiety were higher in those with financial difficulties, in non-Chinese students, in older students and females. In the most extensive review to date the pooled prevalence of depression was 34% (95%CI: 30-38%, 52 studies, n=1,277,755, I2 100%). The prevalence of anxiety was 32% (95% CI: 26-38%, 69 studies I2 100%). Also, anxiety was found at higher rates in older students, in those living alone, and in female students. Only one review concluded the evidence does not suggest a widespread negative effect on mental health in COVID-19 compared with previous years.The overall impact of COVID-19 on the mental health and wellbeing of university students is substantial.AppendicesFull Report - Effects of COVID-19 Restrictions on University Students Mental HealthFiguresFigure 1. PRISMA Flow ChartFigure 2. Included ReviewsFigure 3. Deng 2021 ResultsTablesTable 1. Review Populations and Impacts

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peter mushemi (2024). US Highschool students dataset [Dataset]. https://www.kaggle.com/datasets/petermushemi/us-highschool-students-dataset
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US Highschool students dataset

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27 scholarly articles cite this dataset (View in Google Scholar)
zip(0 bytes)Available download formats
Dataset updated
Apr 14, 2024
Authors
peter mushemi
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Description

The dataset is related to student data, from an educational research study focusing on student demographics, academic performance, and related factors. Here’s a general description of what each column likely represents:

Sex: The gender of the student (e.g., Male, Female). Age: The age of the student. Name: The name of the student. State: The state where the student resides or where the educational institution is located. Address: Indicates whether the student lives in an urban or rural area. Famsize: Family size category (e.g., LE3 for families with less than or equal to 3 members, GT3 for more than 3). Pstatus: Parental cohabitation status (e.g., 'T' for living together, 'A' for living apart). Medu: Mother's education level (e.g., Graduate, College). Fedu: Father's education level (similar categories to Medu). Mjob: Mother's job type. Fjob: Father's job type. Guardian: The primary guardian of the student. Math_Score: Score obtained by the student in Mathematics. Reading_Score: Score obtained by the student in Reading. Writing_Score: Score obtained by the student in Writing. Attendance_Rate: The percentage rate of the student’s attendance. Suspensions: Number of times the student has been suspended. Expulsions: Number of times the student has been expelled. Teacher_Support: Level of support the student receives from teachers (e.g., Low, Medium, High). Counseling: Indicates whether the student receives counseling services (Yes or No). Social_Worker_Visits: Number of times a social worker has visited the student. Parental_Involvement: The level of parental involvement in the student's academic life (e.g., Low, Medium, High). GPA: The student’s Grade Point Average, a standard measure of academic achievement in schools.

This dataset provides a comprehensive look at various factors that might influence a student's educational outcomes, including demographic factors, academic performance metrics, and support structures both at home and within the educational system. It can be used for statistical analysis to understand and improve student success rates, or for targeted interventions based on specific identified needs.

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