Comprehensive demographic dataset for Texas State University Round Rock Campus, Round Rock, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

This dataset tracks annual asian student percentage from 2002 to 2003 for West Texas State School vs. Texas and West Texas State School District

About this dataset

Context

This list ranks the 9 cities in the Texas County, MO by Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Asian Population: This column displays the rank of cities in the Texas County, MO by their Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Asian Population: The Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Texas County Asian Population: This tells us how much of the entire Texas County, MO Asian population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

In California in 2022, 20.5 percent of students enrolled in K-12 public schools were white, 11.9 percent were Asian, and 56.2 percent were Hispanic. In the United States overall, 44.7 percent of K-12 public school students were white, 5.5 percent were Asian, and 28.7 percent were Hispanic.

This dataset tracks annual asian student percentage from 2009 to 2023 for Stephen F Austin State University Charter School District vs. Texas

Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Texas County, OK was 513.00000 Persons in January of 2023, according to the United States Federal Reserve. Historically, Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Texas County, OK reached a record high of 729.00000 in January of 2020 and a record low of 48.00000 in January of 2009. Trading Economics provides the current actual value, an historical data chart and related indicators for Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Texas County, OK - last updated from the United States Federal Reserve on December of 2025.

Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Texas County, MO was 72.00000 Persons in January of 2023, according to the United States Federal Reserve. Historically, Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Texas County, MO reached a record high of 467.00000 in January of 2020 and a record low of 17.00000 in January of 2014. Trading Economics provides the current actual value, an historical data chart and related indicators for Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Texas County, MO - last updated from the United States Federal Reserve on November of 2025.

Types of Abuse, Neglect and Financial Exploitation - A single APS case can have more than one allegation. Neglect is the failure to provide the protection, food, shelter, or care necessary to avoid emotional harm or physical injury. The alleged perpetrator of the neglect may be the victim or the victim's caregiver. There are three types of neglect allegations: Physical Neglect, Medical Neglect, and Mental Health Neglect. Other allegation types include: Financial Exploitation, Physical Abuse, Emotional or Verbal Abuse, or Sexual Abuse. The population totals do not match prior DFPS Data Books, printed or ontline. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but will cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Children, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections for all years from 2014 to 2023 as of December 2023. Visit dfps.state.tx.us for information on all DFPS programs.

Allegation Disposition (Findings): Valid. Based on the standard of preponderance of the evidence, it is more likely than not that the maltreatment occurred. Invalid. Based on the standard of preponderance of the evidence, it is more likely than not that the maltreatment did not occur. Unable to Determine. A preponderance of the available evidence is insufficient to support a finding of Valid or Invalid. Other. The allegation disposition Other is used when an investigation of the allegation was not completed for some reason, e.g. clients died or cases were misclassified. Family Violence is indicated when a validated investigation has a relative perpetrator, excluding those where financial exploitation is the only confirmed allegation. Beginning in Fiscal Year 2015, services provided during the investigation are documented in the investigation stage and not in a separate service stage. The "Other" Disposition category refers to those investigations that workers could not complete, e.g. clients died or cases were misclassified. The population totals do not match prior DFPS Data Books, printed or online. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but will cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Children, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections for all years from 2014 to 2023 as of December 2020. Visit dfps.state.tx.us for information on all DFPS programs.

Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Texas County, OK (B03002006E040139) from 2009 to 2023 about Texas County, OK; asian; OK; non-hispanic; estimate; 5-year; persons; population; and USA.

This dataset tracks annual asian student percentage from 2000 to 2018 for North Texas State Hospital - Afp - Vernon vs. Texas and Vernon Independent School District

ALL FILES ARE LOCATED AT MY REPOSITORY: https://github.com/christianio123/TexasAttendance

Context

I was curious about factors affecting school attendance so I gathered data from school districts around Texas to have a better idea.

Topic/Purpose

The purpose of the project is to help determine factors associated with student attendance in the state of Texas. No population is targeted as an audience for the project, however, anyone associated in education may find the dataset used (and other data attained but not used) helpful in any questions they may have regarding student attendance in Texas for the first two months of the 2020-2021 academic school year. This topic was targeted specifically due to the abnormalities in the current academic school year.

Data

Daily Student Attendance

Majority of the data in this project was collected by school districts around the state of Texas, public census information, and public COVID 19 data. To attain student attendance information, an email was sent out to 40 school districts around the state of Texas on November 2nd, 2020 using the Freedom of Information Act (FOIA). Of those districts, 19 responded with the requested data, while other districts required purchase of the data due to the number of hours associated with labor. Due to ambiguity in the original message sent to districts, varying types of data were collected. The major difference between the data received was the “daily” records of student attendance and a “summary” of student attendance records so far, this academic school year. School districts took between 10 to 15 business days to respond, not including the holidays. The focus of this project is “daily student attendance” in order to find relationships or any influences from external or internal factors on any given school day. Therefore, of the 19 school districts that responded, 11 sent the appropriate data.
The 11 school districts that sent data were (1) Conroe ISD, (2) Cypress-Fairbanks ISD, (3) Floydada ISD, (4) Fort Worth ISD, (5) Pasadena ISD, (6) Snook ISD, (7) Socorro ISD, (8) Klein ISD, (9) Garland ISD, (10) Dallas ISD, and (11) Katy ISD. However, even within these datasets, there were discrepancies, that is, three school districts sent daily attendance data including student grade level but one school district did not include any other information. Also, of the 11 school districts, nine school districts included student attendance broken down by school while three other school districts only had student attendance with no other attributes. This information is important to explain certain steps in analysis preparation later. Variables used from school district datasets included (a) dates, (b) weekdays, (c) school name, (d) school type, (e) district, and (f) grade level.

School Information, County Description, Metropolitan vs. Non-Metropolitan

  In addition to daily student attendance data, two other datasets were used from the Texas Education Agency with data about each school and school district. In one dataset, “Current Schools”, information about each school in the state of Texas was given such as address, principal, county name, district number and much more as of May 2020. From this dataset, variables selected include (a) school name, (b) school zip, (3) district number, (4) and school type. In the second dataset, “District Type”, attributes of each school district were given such as whether the school district was considered major urban, independent town, or a rural area. From “District Type” dataset, selected variables used were (a) district, district number, Texas Education Agency (TEA) description, and National Center of Education Statistics (NCES). To determine if a county is metropolitan or non-metropolitan, a dataset from the Texas Health and Human Services was used. Selected variables from this dataset include (a) county name and (b) metro area. 

Other Factors: COVID-19

 Student attendance has been noticeably different this academic school year, therefore live COVID-19 data was attained from the New York Times to examine for any relationship. This dataset is updated daily with data being available in three formats (country, state, and county). From this dataset, variables selected were both COVID-19 cases by state, and by county.

Other Factors: Demographics

Each school has a unique student population, therefore census data from 2018 (with best estimate of today’s current population) was used to find the makeup of the population surrounding a school by zip code. From the census data, variables selected were zip code, race/ethnicity, medium income, unemployment rate, and education. These variables were selected to determine differences between school attendance based on the makeup of the population surrounding the school.

Other Factors: Weather

  Weather seems to have an impact on student attendance at schools, so weather data has been included based on county measures.

DFPS sets priorities for the delivery of protective services. In establishing priorities, DFPS defines timeframes for conducting initial face-to-face interviews with alleged victims. The priorities are based on severity and immediacy of alleged threat to the life or physical safety of the alleged victim. (40 Texas Administrative Code §705.2101) The initial face-to-face contact with the alleged victim is conducted according to the following priorities: Priority 1: Allegations that the victim is in a state of serious harm or is in danger of death from abuse or neglect. APS makes face-to-face contact within 24 hours of SWI’s receipt of Priority I allegations. Priority 2: Allegations that the victim is abused, neglected, or financially exploited and, as a result, is at risk of serious harm. APS makes face-to-face contact within three calendar days of SWI’s receipt of Priority II allegations. Priority 3: All other allegations that the victim is in a state of abuse or neglect. APS makes face-to-face contact within seven calendar days of SWI’s receipt of Priority III allegations. Priority 4: Allegations of financial exploitation when there is no danger of imminent impoverishment or deprivation of basic needs. APS makes face-to-face contact within 14 calendar days of SWI’s receipt of Priority IV allegations. Inclusion is based on the Intake Closure Date.

This dataset tracks annual asian student percentage from 2005 to 2023 for Ron Jackson State Juvenile Correctional Complex Unit I High School vs. Texas and Ron Jackson State Juvenile Corr Complex Unit I School District

This dataset tracks annual asian student percentage from 2019 to 2023 for Sam Houston State University Charter School District vs. Texas

Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Harris County, TX (B03002006E048201) from 2009 to 2023 about Harris County, TX; asian; Houston; non-hispanic; estimate; TX; 5-year; persons; population; and USA.

Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Robertson County, TX (B03002006E048395) from 2009 to 2023 about Robertson County, TX; College Station; asian; non-hispanic; estimate; TX; 5-year; persons; population; and USA.

Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Brewster County, TX (B03002006E048043) from 2009 to 2023 about Brewster County, TX; asian; non-hispanic; estimate; TX; 5-year; persons; population; and USA.

This dataset tracks annual asian student percentage from 2004 to 2011 for Al Price State Juvenile Correctional Facility High School vs. Texas and Al Price State Juvenile Correctional Facility School District

This dataset tracks annual asian student percentage from 2002 to 2003 for J W Hamilton Junior State School vs. Texas and J W Hamilton Jr State School District