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.

Data product is provided by ASL Marketing. It contains current college students who are attending colleges and universities nationwide. Connect with this market by: Class Year Field of Study Home/School address College Attending Ethnicity School Type Region Sports Conference Gender eSports Email

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.

We know that students at elite universities tend to be from high-income families, and that graduates are more likely to end up in high-status or high-income jobs. But very little public data has been available on university admissions practices. This dataset, collected by Opportunity Insights, gives extensive detail on college application and admission rates for 139 colleges and universities across the United States, including data on the incomes of students. How do admissions practices vary by institution, and are wealthy students overrepresented?

Motivation

Education equality is one of the most contested topics in society today. It can be defined and explored in many ways, from accessible education to disabled/low-income/rural students to the cross-generational influence of doctorate degrees and tenure track positions. One aspect of equality is the institutions students attend. Consider the “Ivy Plus” universities, which are all eight Ivy League schools plus MIT, Stanford, Duke, and Chicago. Although less than half of one percent of Americans attend Ivy-Plus colleges, they account for more than 10% of Fortune 500 CEOs, a quarter of U.S. Senators, half of all Rhodes scholars, and three-fourths of Supreme Court justices appointed in the last half-century.

A 2023 study (Chetty et al, 2023) tried to understand how these elite institutions affect educational equality:

Do highly selective private colleges amplify the persistence of privilege across generations by taking students from high-income families and helping them obtain high-status, high-paying leadership positions? Conversely, to what extent could such colleges diversify the socioeconomic backgrounds of society’s leaders by changing their admissions policies?

To answer these questions, they assembled a dataset documenting the admission and attendance rate for 13 different income bins for 139 selective universities around the country. They were able to access and link not only student SAT/ACT scores and high school grades, but also parents’ income through their tax records, students’ post-college graduate school enrollment or employment (including earnings, employers, and occupations), and also for some selected colleges, their internal admission ratings for each student. This dataset covers students in the entering classes of 2010–2015, or roughly 2.4 million domestic students.

They found that children from families in the top 1% (by income) are more than twice as likely to attend an Ivy-Plus college as those from middle-class families with comparable SAT/ACT scores, and two-thirds of this gap can be attributed to higher admission rates with similar scores, with the remaining third due to the differences in rates of application and matriculation (enrollment conditional on admission). This is not a shocking conclusion, but we can further explore elite college admissions by socioeconomic status to understand the differences between elite private colleges and public flagships admission practices, and to reflect on the privilege we have here and to envision what a fairer higher education system could look like.

Data

The data has been aggregated by university and by parental income level, grouped into 13 income brackets. The income brackets are grouped by percentile relative to the US national income distribution, so for instance the 75.0 bin represents parents whose incomes are between the 70th and 80th percentile. The top two bins overlap: the 99.4 bin represents parents between the 99 and 99.9th percentiles, while the 99.5 bin represents parents in the top 1%.

Each row represents students’ admission and matriculation outcomes from one income bracket at a given university. There are 139 colleges covered in this dataset.

The variables include an array of different college-level-income-binned estimates for things including attendance rate (both raw and reweighted by SAT/ACT scores), application rate, and relative attendance rate conditional on application, also with respect to specific test score bands for each college and in/out-of state. Colleges are categorized into six tiers: Ivy Plus, other elite schools (public and private), highly selective public/private, and selective public/private, with selectivity generally in descending order. It also notes whether a college is public and/or flagship, where “flagship” means public flagship universities. Furthermore, they also report the relative application rate for each income bin within specific test bands, which are 50-point bands that had the most attendees in each school tier/category.

Several values are reported in “test-score-reweighted” form. These values control for SAT score: they are calculated separately for each SAT score value, then averaged with weights based on the distribution of SAT scores at the institution.

Note that since private schools typically don’t differentiate between in-...

Analysis of ‘U.S. News and World Report’s College Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/flyingwombat/us-news-and-world-reports-college-data on 30 September 2021.

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

Context

Statistics for a large number of US Colleges from the 1995 issue of US News and World Report.

Content

A data frame with 777 observations on the following 18 variables.

Private A factor with levels No and Yes indicating private or public university

Apps Number of applications received

Accept Number of applications accepted

Enroll Number of new students enrolled

Top10perc Pct. new students from top 10% of H.S. class

Top25perc Pct. new students from top 25% of H.S. class

F.Undergrad Number of fulltime undergraduates

P.Undergrad Number of parttime undergraduates

Outstate Out-of-state tuition

Room.Board Room and board costs

Books Estimated book costs

Personal Estimated personal spending

PhD Pct. of faculty with Ph.D.’s

Terminal Pct. of faculty with terminal degree

S.F.Ratio Student/faculty ratio

perc.alumni Pct. alumni who donate

Expend Instructional expenditure per student

Grad.Rate Graduation rate

Source

This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.

The dataset was used in the ASA Statistical Graphics Section’s 1995 Data Analysis Exposition.

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

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.

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

This data (Age, MEQ, BMI) is from 384 university students enrolled in health and physical exercise (HPE) courses at a mid-sized university in the West South Central United States. The data are from a two-semester period (Fall 2019 & Spring 2020) and were collated and de-identified by members of the institutional research team before being given to the research team for analysis. This study does not include data from students who opted out (the default option), students with BMI values below 14.5 kg·m-2 or above 49.4 kg·m-2, and students whose age was below 16 or above 24.

The dataset contains Academic-year- and Country-wise historically compiled data on the total number of International students enrolled for studying Undergraduate, Graduate, Non-Degree and Optional Practical Training (OPT) courses in the United States of America (USA).

Context

This dataset contains the US News rankings of the best American universities of undergraduate programs. This is how US News ranks the colleges: "We calculated 10 distinct overall rankings where colleges and universities were grouped by their academic missions. For each ranking, the sum of weighted, normalized values across 17 indicators of academic quality determine each school's overall score and, by extension, its overall rank. The top performer(s) in each ranking displays an overall score of 100. Others' overall scores are on a 0-99 scale reflecting the distance from their ranking's top-performing school(s). Those placing outside the top 75% display their ranking's bottom quartile range (e.g., No. 90-120) instead of their individual ranks (e.g., No. 102)."

Content

This dataset contains the rankings of 392 American universities based on their undergraduate programs. It also contains the tuitions and enrollment numbers of each university. 2 colleges don't have tuition data, so it is labelled -1.

Acknowledgements

We acknowledge US News for providing these rankings.

Inspiration

As a high schooler applying to undergraduate programs in America, it would be useful to know which colleges are best, and to compare tuitions and enrollment numbers.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES SCHOOL ENROLLMENT - DP02 Universe - Population 3 Year and over enrolled in school Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to “include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree.” Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.

School enrollment data are used to assess the socioeconomic condition of school-age children. Government agencies also require these data for funding allocations and program planning and implementation.

Data on school enrollment and grade or level attending were derived from answers to Question 10 in the 2015 American Community Survey (ACS). People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to “include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree.” Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.

School enrollment is only recorded if the schooling advances a person toward an elementary school certificate, a high school diploma, or a college, university, or professional school (such as law or medicine) degree. Tutoring or correspondence schools are included if credit can be obtained from a public or private school or college. People enrolled in “vocational, technical, or business school” such as post secondary vocational, trade, hospital school, and on job training were not reported as enrolled in school. Field interviewers were instructed to classify individuals who were home schooled as enrolled in private school. The guide sent out with the mail questionnaire includes instructions for how to classify home schoolers.

Enrolled in Public and Private School – Includes people who attended school in the reference period and indicated they were enrolled by marking one of the questionnaire categories for “public school, public college,” or “private school, private college, home school.” The instruction guide defines a public school as “any school or college controlled and supported primarily by a local, county, state, or federal government.” Private schools are defined as schools supported and controlled primarily by religious organizations or other private groups. Home schools are defined as “parental-guided education outside of public or private school for grades 1-12.” Respondents who marked both the “public” and “private” boxes are edited to the first entry, “public.”

Grade in Which Enrolled – From 1999-2007, in the ACS, people reported to be enrolled in “public school, public college” or “private school, private college” were classified by grade or level according to responses to Question 10b, “What grade or level was this person attending?” Seven levels were identified: “nursery school, preschool;” “kindergarten;” elementary “grade 1 to grade 4” or “grade 5 to grade 8;” high school “grade 9 to grade 12;” “college undergraduate years (freshman to senior);” and “graduate or professional school (for example: medical, dental, or law school).”

In 2008, the school enrollment questions had several changes. “Home school” was explicitly included in the “private school, private college” category. For question 10b the categories changed to the following “Nursery school, preschool,” “Kindergarten,” “Grade 1 through grade 12,” “College undergraduate years (freshman to senior),” “Graduate or professional school beyond a bachelor’s degree (for example: MA or PhD program, or medical or law school).” The survey question allowed a write-in for the grades enrolled from 1-12.

Question/Concept History – Since 1999, the ACS enrollment status question (Question 10a) refers to “regular school or college,” while the 1996-1998 ACS did not restrict reporting to “regular” school, and contained an additional category for the “vocational, technical or business school.” The 1996-1998 ACS used the educational attainment question to estimate level of enrollment for those reported to be enrolled in school, and had a single year write-in for the attainment of grades 1 through 11. Grade levels estimated using the attainment question were not consistent with other estimates, so a new question specifically asking grade or level of enrollment was added starting with the 1999 ACS questionnaire.

Limitation of the Data – Beginning in 2006, the population universe in the ACS includes people living in group quarters. Data users may see slight differences in levels of school enrollment in any given geographic area due to the inclusion of this population. The extent of this difference, if any, depends on the type of group quarters present and whether the group quarters population makes up a large proportion of the total population. For example, in areas that are home to several colleges and universities, the percent of individuals 18 to 24 who were enrolled in college or graduate school would increase, as people living in college dormitories are now included in the universe.

This dataset explore the Residence and migration of all freshmen students in degree-granting institutions who graduated from high school in the previous 12 months, by state: Fall 2004 NOTE: Includes all first-time postsecondary students enrolled at reporting institutions. Degree-granting institutions grant associate's or higher degrees and participate in Title IV federal financial aid programs. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Spring 2005. (This table was prepared September 2005.) http://nces.ed.gov/programs/digest/d06/tables/dt06_208.asp Accessed on 12 November 2007

This dataset provides information for Academic Years 2017-2021 which included: By College and VCCS System:

1) Annual Headcount and FTEs 2) Gender (categories are: Female & Male; Unknown may be inferred) 3) Ethnicity (categories are: American Indian & Alaskan Native, Asian, Black & African-American, Native Hawaiian & Pacific Islander, Hispanic, Two or More Races, Unknown/Not Specified, and White) 4) Age (categories are: 17 and Under, 18-19, 20-21, 22-24, 25-29, 30-34, 35-39, 40-49, 50-64, & 65 and Over) 5) 18-Month Outcomes for Dual-Enrolled High School Grads by Year (categories are: Total Grads, Continued in any Higher Ed program, Employed with no Higher Ed, and Unknown) 6) 18-Month Outcomes for VCCS Graduates by Year (categories are: Total Grads, Continued at VCCS, Transferred to a 4yr college, Employed with no Higher Ed, and Unknown)

For Fiscal Years 2018-2021, by Service Area and VCCS System:

1) Fast Forward Credentialers Employed by Fiscal Year (categories are: Total Distinct Students, Employed within 6 Months, Employed within 12 Months, and Employed within 18 Months)

Notes:

1) Headcounts are Unduplicated student counts. 2) One FTE represents 30 credit hours of classes taken by a student over an academic year and is calculated on an annual basis by taking the total credit hours taught divided by 30. 3) 2017 Fiscal Year Fast Forward data was not included as it was considered incomplete- the Fast Forward program began in 2017 and did not encompass all areas for the entire year.
4) In Workforce (Fast Forward data) the service region for the Richmond Metro Area is called CCWA (Community College Workforce Alliance) and combines data for Brightpoint and J Sargeant Reynolds. 4a) Therefore, there are no Reynolds data entries for Fast Forward variables. All CCWA data is listed under Brightpoint for this portion of the data set.
5) 18-Month Outcomes for Fast Forward Credentialers are cumulative (6 months to 12 months to 18 months)

The primary research objective of this study was to examine the prevalence, nature, and reporting of various types of sexual assault experienced by university students in an effort to inform the development of targeted intervention strategies. In addition, the study had two service-oriented objectives: (1) to educate students about various types of sexual assault, how they can maximize their safety, and what they can do if they or someone they know has been victimized and (2) to provide students with information about the campus and community resources that are available should they need assistance or have any concerns or questions. The study involved a Web-based survey of random samples of undergraduate students at two large public universities, one located in the South (University 1) and one located in the Midwest (University 2). Researchers drew random samples of students aged 18-25 and enrolled at least three-quarters' time at each university to participate in the study. The survey was administered in the winter of 2005-2006, and a total of 5,446 undergraduate women and 1,375 undergraduate men participated for a grand total of 6,821 respondents. Sampled students were sent an initial recruitment e-mail that described the study, provided a unique study ID number, and included a hyperlink to the study Web site. During each of the following weeks, students who had not completed the survey were sent follow-up e-mails and a hard-copy letter encouraging them to participate. The survey was administered anonymously and was designed to be completed in an average of 15 minutes. Respondents were provided with a survey completion code that, when entered with their study ID number at a separate Web site, enabled them to obtain a $10 Amazon.com gift certificate. The survey was divided into six modules. The Background Information module included survey items on demographics, school classification (year of study, year of enrollment, transfer status), residential characteristics, academic performance, and school involvement. An Alcohol and Other Drug Use module generated a number of measures of alcohol and drug use, and related substance use behaviors. A Dating module included items on sexual orientation, dating, consensual sexual activity, and dating violence. The Experiences module was developed after extensive reviews of past surveys of sexual assault and generated information on physically forced sexual assault and incapacitated sexual assault. For both physically forced and incapacitated sexual assault, information was collected on completed and attempted assaults experienced before entering college and since entering college. For male respondents, a Behaviors module asking about the perpetration of the same types of sexual assault covered in the Experiences module was included. The final module of the survey covered attitudes about sexual assault and attitudes about the survey. The data file contains 747 variables.

This series of 11 datasets is drawn from Rhoads, Edward J. M. Stepping Forth into the World: The Chinese Educational Mission to the United States, 1872-81. Hong Kong University Press, 2011. They document the 120 young Chinese who participated in the pioneering Chinese Educational Mission (CEM) in the United States (1872-1881). The first 8 files are drawn directly from the tables in Rhoads: Table 2.1 CEM students, by detachment (p.14-17) Table 5.1. Initial host family assignments (p.51-54) Table 7.1. CEM students in middle schools (by state and locality) (p. 90-94) Table 7.2 CEM students in public high schools (by state and locality) (p.96-99) Table 7.3 CEM students in private academies (by state and locality) (p.99-100) Table 8.1 CEM students in colleges (by academic year of enrollment) (p.116-118) Table 9.1 Deaths, dismissals, and withdrawals from the CEM (by date) (p.136) Table 9.2 CEM students in the June 1880 census (p.138-142) Based on these tables, I created three synthetic datasets which can be used for statistical and network analyses: cem_attributes: students' vital attributes, including their multiple names and transliteration, date and place of birth, and other attribute data (one row for each individual). cem_host: students' host families in the United States cem_education: students' educational curricula Each file contains two tabs, one for the data (data), one for the description of variables (key). Grey columns refer to the unstructured information given in the original source.

This dataset provides comprehensive information about various Data Science and Analytics master's programs offered in the United States. It includes details such as the program name, university name, annual tuition fees, program duration, location of the university, and additional information about the programs.

Column Descriptions:

• Subject Name: The name or field of study of the master's program, such as Data Science, Data Analytics, or Applied Biostatistics.

• University Name: The name of the university offering the master's program.

• Per Year Fees: The tuition fees for the program, usually given in euros per year. For some programs, the fees may be listed as "full" or "full-time," indicating a lump sum for the entire program or for full-time enrollment, respectively.

• About Program: A brief description or overview of the master's program, providing insights into its curriculum, focus areas, and any unique features.

• Program Duration: The duration of the master's program, typically expressed in years or months.

• University Location: The location of the university where the program is offered, including the city and state.

• Program Name: The official name of the master's program, often indicating its degree type (e.g., M.Sc. for Master of Science) and format (e.g., full-time, part-time, online).

About this dataset

Context

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

Key observations

There is a majority of male population, with 53.83% 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 State College is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of State College 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 State College Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

There is a slight majority of female population, with 52.15% 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 College Place is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of College 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 College Place Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of North College Hill by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for North College Hill. The dataset can be utilized to understand the population distribution of North College Hill by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in North College Hill. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for North College Hill.

Key observations

Largest age group (population): Male # 30-34 years (847) | Female # 5-9 years (816). 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.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

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.

Variables / Data Columns

• Age Group: This column displays the age group for the North College Hill population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the North College Hill is shown in the following column.
• Population (Female): The female population in the North College Hill is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in North College Hill for each age group.

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 North College Hill Population by Gender. You can refer the same here