Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of State College by race. It includes the population of State College across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of State College across relevant racial categories.
Key observations
The percent distribution of State College population by race (across all racial categories recognized by the U.S. Census Bureau): 80.12% are white, 3.72% are Black or African American, 0.19% are American Indian and Alaska Native, 10.35% are Asian, 0.03% are Native Hawaiian and other Pacific Islander, 0.36% are some other race and 5.23% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for State College Population by Race & Ethnicity. You can refer the same here
According to a survey conducted in 2023, ** percent of Black Americans said that they approved of selective colleges and universities taking race and ethnicity into account in admissions decisions in order to increase diversity at school in the United States, while ** percent of Hispanic Americans and ** percent of Asian Americans shared this belief.
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Graph and download economic data for Consumer Unit Characteristics: Percent White, Asian, and All Other Races, Not Including African American by Highest Education: College Graduate: Master's, Professional, Doctoral Degree (CXUWHTNDOTHLB1409M) from 2012 to 2023 about doctoral degree, consumer unit, professional, asian, tertiary schooling, white, education, percent, and USA.
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Graph and download economic data for Consumer Unit Characteristics: Percent College by Race: White and All Other Races, Not Including Black or African American (CXU980310LB0903M) from 2003 to 2023 about consumer unit, tertiary schooling, white, education, percent, and USA.
In 2022, there were approximately 107,700 students with American Indian or Alaskan Native heritage enrolled at a university in the United States. This is a slight increase from the previous year, when there were 106,600 students with American Indian or Alaska Native heritage enrolled in postsecondary education.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of State College by race. It includes the distribution of the Non-Hispanic population of State College across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of State College across relevant racial categories.
Key observations
Of the Non-Hispanic population in State College, the largest racial group is White alone with a population of 31,373 (81.20% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for State College Population by Race & Ethnicity. You can refer the same here
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Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, Two or More Races, Two Races Excluding Some Other Race, and Three or More Races (5-year estimate) in Centre County, PA (B03002011E042027) from 2009 to 2023 about Centre County, PA; State College; PA; non-hispanic; estimate; persons; 5-year; population; and USA.
In 2021, about 20.6 percent of postsecondary students in the United States were Hispanic. This is a slight increase from 20.3 percent in the previous year. In that same year, White students made up more than half of postsecondary students, at 53.4 percent.
In the 2024 academic year, just over 540 thousand students competed in NCAA sports across the United States. White NCAA athletes made up just over 60 percent of this athlete population, with a total of 332,016 white athletes competing in NCAA college sports in this year.
College football takes place in organized leagues between teams of students from different universities in the U.S. and Canada. The leagues are organized by the NCAA, which is the sports association that organizes a wide range of sports for colleges and students. In a survey conducted in April 2023, around 23 percent of Black respondents stated that they were avid fans of college football in the United States.
https://www.icpsr.umich.edu/web/ICPSR/studies/36961/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36961/terms
The Community College Civic Outcomes Survey, Spring 2017 study examines the individual and institutional factors associated with greater civic agency, capacity, behavior, and knowledge among college students. In Spring 2017, two surveys were digitally administered at 8 community colleges, or community college systems. These colleges were purposively selected for diversity in terms of geography, campus setting, size, and the racial and ethnic composition of their student bodies. This data includes a sample of 1,168 surveys from those collected. The Civic Outcomes Survey (COS) was administered to students, and included questions related to voting, political and community engagement, civic knowledge, and leadership development. The Institutional Questionnaire (IQ), was admitted to each college's liaisons to The Democracy Commitment (TDC), and included questions related to college-level factors known to influence student engagement. These questions assessed for institutional intentionality towards civic engagement through college missions and strategic planning, as well as academic and faculty focus on civic involvement. Both instruments were previously tested in a small regional pilot and were subsequently refined to allow for greater response variability. Demographic variables include race, income, gender, and enrollment status.
This statistic shows the percentage of students identifying as first-generation in the United States in 2016, by gender and ethnicity. As of 2016, about ** percent of the first-generation American students, broken down by gender, were female. Almost ** percent of the first-generation students identified themselves as Native Americans in the United States in 2016.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau practices "data suppression", filtering some block groups from demographic publication because they do not meet a population threshold. This practice...
https://www.icpsr.umich.edu/web/ICPSR/studies/8342/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/8342/terms
This summary statistics data file contains a complete or 100-percent count of all persons in group quarters by sex and age, including ages under 1 to 74 with a category for ages 75 and over, as well as the total. The distribution is repeated for 18 race/Hispanic groups. Population in group quarters includes persons in institutional group quarters such as homes, schools, hospitals, or wards for the physically and mentally handicapped, hospitals or wards for mental, tubercular, or chronically ill patients, homes for unwed mothers, nursing, convalescent, and rest homes for the aged and dependent, orphanages, and correctional institutions. Noninstitutional group quarters include rooming and boarding houses, general hospitals, including nurses' and interns' dormitories, college students' dormitories, religious group quarters, and similar housing. Demographic items specify age, sex, state of birth, race, ethnicity, marital status, education, income, and type of group quarters lived in. Data are available for all counties and independent cities in the United States.
https://www.icpsr.umich.edu/web/ICPSR/studies/2419/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/2419/terms
The principal purposes of this national longitudinal study of the higher education system in the United States are to describe the characteristics of new college freshmen and to explore the effects of college on students. For each wave of this survey, each student completes a questionnaire during freshman orientation or registration that asks for information on academic skills and preparation, high school activities and experiences, educational and career plans, majors and careers, student values, and financing college. Other questions elicit demographic information, including sex, age, parental education and occupation, household income, race, religious preference, and state of birth. Specific questions asked of respondents in the 1985 survey pertained to students' self-ratings of their academic ability, artistic ability, physical health, self-confidence, and writing ability. Other questions provided information regarding students' institutional race, institutional type, institutional sex, as well as their tuition fees, transportation costs, and books and supplies expenses.
description: This dataset is imported from the US Department of Commerce, National Telecommunications and Information Administration (NTIA) and its "Data Explorer" site. The underlying data comes from the US Census 1. dataset: Specifies the month and year of the survey as a string, in "Mon YYYY" format. The CPS is a monthly survey, and NTIA periodically sponsors Supplements to that survey. 2. variable: Contains the standardized name of the variable being measured. NTIA identified the availability of similar data across Supplements, and assigned variable names to ease time-series comparisons. 3. description: Provides a concise description of the variable. 4. universe: Specifies the variable representing the universe of persons or households included in the variable's statistics. The specified variable is always included in the file. The only variables lacking universes are isPerson and isHouseholder, as they are themselves the broadest universes measured in the CPS. 5. A large number of *Prop, *PropSE, *Count, and *CountSE columns comprise the remainder of the columns. For each demographic being measured (see below), four statistics are produced, including the estimated proportion of the group for which the variable is true (*Prop), the standard error of that proportion (*PropSE), the estimated number of persons or households in that group for which the variable is true (*Count), and the standard error of that count (CountSE). DEMOGRAPHIC CATEGORIES 1. us: The usProp, usPropSE, usCount, and usCountSE columns contain statistics about all persons and households in the universe (which represents the population of the fifty states and the District and Columbia). For example, to see how the prevelance of Internet use by Americans has changed over time, look at the usProp column for each survey's internetUser variable. 2. age: The age category is divided into five ranges: ages 3-14, 15-24, 25-44, 45-64, and 65+. The CPS only includes data on Americans ages 3 and older. Also note that household reference persons must be at least 15 years old, so the age314 columns are blank for household-based variables. Those columns are also blank for person-based variables where the universe is "isAdult" (or a sub-universe of "isAdult"), as the CPS defines adults as persons ages 15 or older. Finally, note that some variables where children are technically in the univese will show zero values for the age314* columns. This occurs in cases where a variable simply cannot be true of a child (e.g. the workInternetUser variable, as the CPS presumes children under 15 are not eligible to work), but the topic of interest is relevant to children (e.g. locations of Internet use). 3. work: Employment status is divided into "Employed," "Unemployed," and "NILF" (Not in the Labor Force). These three categories reflect the official BLS definitions used in official labor force statistics. Note that employment status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by work status, even if they are otherwise considered part of the universe for the variable of interest. 4. income: The income category represents annual family income, rather than just an individual person's income. It is divided into five ranges: below $25K, $25K-49,999, $50K-74,999, $75K-99,999, and $100K or more. Statistics by income group are only available in this file for Supplements beginning in 2010; prior to 2010, family income range is available in public use datasets, but is not directly comparable to newer datasets due to the 2010 introduction of the practice of allocating "don't know," "refused," and other responses that result in missing data. Prior to 2010, family income is unkown for approximately 20 percent of persons, while in 2010 the Census Bureau began imputing likely income ranges to replace missing data. 5. education: Educational attainment is divided into "No Diploma," "High School Grad," "Some College," and "College Grad." High school graduates are considered to include GED completers, and those with some college include community college attendees (and graduates) and those who have attended certain postsecondary vocational or technical schools--in other words, it signifies additional education beyond high school, but short of attaining a bachelor's degree or equivilent. Note that educational attainment is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by education, even if they are otherwise considered part of the universe for the variable of interest. 6. sex: "Male" and "Female" are the two groups in this category. The CPS does not currently provide response options for intersex individuals. 7. race: This category includes "White," "Black," "Hispanic," "Asian," "Am Indian," and "Other" groups. The CPS asks about Hispanic origin separately from racial identification; as a result, all persons identifying as Hispanic are in the Hispanic group, regardless of how else they identify. Furthermore, all non-Hispanic persons identifying with two or more races are tallied in the "Other" group (along with other less-prevelant responses). The Am Indian group includes both American Indians and Alaska Natives. 8. disability: Disability status is divided into "No" and "Yes" groups, indicating whether the person was identified as having a disability. Disabilities screened for in the CPS include hearing impairment, vision impairment (not sufficiently correctable by glasses), cognitive difficulties arising from physical, mental, or emotional conditions, serious difficulty walking or climbing stairs, difficulty dressing or bathing, and difficulties performing errands due to physical, mental, or emotional conditions. The Census Bureau began collecting data on disability status in June 2008; accordingly, this category is unavailable in Supplements prior to that date. Note that disability status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by disability status, even if they are otherwise considered part of the universe for the variable of interest. 9. metro: Metropolitan status is divided into "No," "Yes," and "Unkown," reflecting information in the dataset about the household's location. A household located within a metropolitan statistical area is assigned to the Yes group, and those outside such areas are assigned to No. However, due to the risk of de-anonymization, the metropolitan area status of certain households is unidentified in public use datasets. In those cases, the Census Bureau has determined that revealing this geographic information poses a disclosure risk. Such households are tallied in the Unknown group. 10. scChldHome: 11.
In 2024, white respondents had the highest rates of confidence about being able to meet the costs of a college education in the United States. Meanwhile, ** percent of Hispanic respondents and ** of Black respondents were completely confident about being able to pay the costs of college education. On the other side of the spectrum, *** percent of white and Black respondents were unconfident about being able to meet these costs.
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.
This statistic shows the percentage of the White, non-Hispanic population aged between 25 and 29 with a bachelor's or a higher level degree in the United States from 1975 to 2021, by gender. In 2021, about ** percent of white, non-Hispanic females had attained at least a bachelor's degree in the United States.
https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de439897https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de439897
Abstract (en): The Recent College Graduates (RCG) survey estimates the potential supply of newly qualified teachers in the United States and explores the immediate post-degree employment and education experiences of individuals obtaining bachelor's or master's degrees from American colleges and universities. The RCG survey, which focuses heavily, but not exclusively, on those graduates qualified to teach at the elementary and secondary levels, is designed to meet the following objectives: (1) to determine how many graduates become eligible or qualified to teach for the first time and how many are employed as teachers in the year following graduation, by teaching field, (2) to examine the relationships among courses taken, student achievement, and occupational outcomes, and (3) to monitor unemployment rates and average salaries of graduates by field of study. The RCG survey collects information on education and employment of all graduates (date of graduation, field of study, whether newly qualified to teach, further enrollment, financial aid, employment status, and teacher employment characteristics) as well as standard demographic characteristics such as earnings, age, marital status, sex, and race/ethnicity. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Students within one year of attaining a bachelor's or a master's degree from an American college or university. A two-stage stratified sampling approach was employed. The first stage consisted of drawing a sample of bachelor's and master's degree-granting institutions from Higher Education General Information Survey (HEGIS)/Integrated Postsecondary Education Data System (IPEDS) completions files. Institutions were stratified by control (public or private), by region, and by the proportion of degrees awarded in the field of education (over or under a specified number). Within each of these strata, institutions were selected according to size (size being measured by the sum of bachelor's and master's degrees awarded that year). The second stage consisted of the selection of a core sample of graduates (bachelor's and master's degree recipients) who received their degrees from the sampled institutions during the 1976-1977 academic year. Sampling rates of graduates differed by major field of study. The institution sample consisted of 300 institutions of which 30 were Historically Black Colleges (HBCs). The graduate sample was stratified by degree received and major field of study (vocational education, special education, other education, and noneducation). Data are representative at the national level. 2001-01-05 SAS and SPSS data definition statements have been created for this collection. Also, the codebook and data collection instrument were converted to a PDF file. The codebook and data collection instrument are provided by ICPSR as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of State College by race. It includes the population of State College across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of State College across relevant racial categories.
Key observations
The percent distribution of State College population by race (across all racial categories recognized by the U.S. Census Bureau): 80.12% are white, 3.72% are Black or African American, 0.19% are American Indian and Alaska Native, 10.35% are Asian, 0.03% are Native Hawaiian and other Pacific Islander, 0.36% are some other race and 5.23% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for State College Population by Race & Ethnicity. You can refer the same here