About this dataset

Context

The dataset tabulates the population of Liberty Hill by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Liberty Hill. The dataset can be utilized to understand the population distribution of Liberty Hill by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Liberty 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 Liberty Hill.

Key observations

Largest age group (population): Male # 0-4 years (397) | Female # 35-39 years (650). 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 Liberty Hill population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Liberty Hill is shown in the following column.
• Population (Female): The female population in the Liberty 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 Liberty 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 Liberty Hill Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Seven Points by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Seven Points. The dataset can be utilized to understand the population distribution of Seven Points by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Seven Points. 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 Seven Points.

Key observations

Largest age group (population): Male # 0-4 years (106) | Female # 30-34 years (70). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Seven Points population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Seven Points is shown in the following column.
• Population (Female): The female population in the Seven Points 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 Seven Points 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 Seven Points Population by Gender. You can refer the same here

APS may provide non-purchased services or purchased services. The chart compares these two types of services. Non-purchased services can include services provided directly by APS staff or services provided by other entities, including social casework, legal actions, or services provided by other government agencies or community organizations. APS may purchase services for clients using Purchased Client Services (PCS) funds. Purchased services may include short-term shelter, food, medication, health services, financial help with rent or utilities, transportation, and minor home repair. All other available resources must be used where feasible before purchased client services are initiated. Visit dfps.state.tx.us for information on all DFPS programs.

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.

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

This data set is aimed at learning more about the lives of Texas adults. Specifically, the data set contains information on seven major aspects of Texans' lives: civic engagement and attitudes; volunteering; organizational memberships and giving behaviors; personality; physical and mental health; health behaviors; religious activities and beliefs. The dataset also includes information about respondents' demographic characteristics.

Children in DFPS custody are those for whom a court has appointed DFPS legal responsibility through temporary or permanent managing conservatorship or other court ordered legal basis. This chart includes any child in DFPS custody on August 31 of the fiscal year. A description of the different types of legal statuses is in the CPS glossary: https://www.dfps.texas.gov/About_DFPS/Data_Book/Child_Protective_Services/Resources/glossary.asp Visit dfps.texas.gov for information on all DFPS programs

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

About this dataset

Context

The dataset tabulates the Texas County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Texas County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Texas County was 20,371, a 0.65% decrease year-by-year from 2022. Previously, in 2022, Texas County population was 20,505, a decline of 1.65% compared to a population of 20,849 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Texas County increased by 178. In this period, the peak population was 22,052 in the year 2013. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Texas County is shown in this column.
• Year on Year Change: This column displays the change in Texas County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Texas County Population by Year. You can refer the same here

This chart counts children who exited DFPS custody to adoption during the fiscal year. To be adopted, a court must have terminated parental rights, the child must have lived with the adoptive family for at least 6 months, the family must have been approved for adoption through a licensed child placing agency and a court must have ordered legal custody to the adoptive parents.

Visit dfps.state.tx.us for information on all DFPS programs

This dataset shows the incomes of residents. The data is part of the Census Transportation Planning Package (CTPP), and is the result of a cooperative effort between various groups including the State Departments of Transportation, U.S. Census Bureau, and the Federal Highway Administration. The data is a special tabulation of responses from households completing the decennial census long form. The data was collected in 2000 and is shown at tract level.

This dataset shows the origin and race of residents. The data is part of the Census Transportation Planning Package (CTPP), and is the result of a cooperative effort between various groups including the State Departments of Transportation, U.S. Census Bureau, and the Federal Highway Administration. The data is a special tabulation of responses from households completing the decennial census long form. The data was collected in 2000 and is shown at tract level.

Comprehensive demographic dataset for Leander, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

The Hispanic EPESE provides data on risk factors for mortality and morbidity in Mexican Americans in order to contrast how these factors operate differently in non-Hispanic White Americans, African Americans, and other major ethnic groups. The Wave 7 dataset comprises the sixth follow-up of the baseline Hispanic EPESE (HISPANIC ESTABLISHED POPULATIONS FOR THE EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1993-1994: [ARIZONA, CALIFORNIA, COLORADO, NEW MEXICO, AND TEXAS] [ICPSR 2851]). The baseline Hispanic EPESE collected data on a representative sample of community-dwelling Mexican Americans, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. The public-use data cover demographic characteristics (age, sex, type of Hispanic race, income, education, marital status, number of children, employment, and religion), height, weight, social and physical functioning, chronic conditions, related health problems, health habits, self-reported use of dental, hospital, and nursing home services, and depression. Subsequent follow-ups provide a cross-sectional examination of the predictors of mortality, changes in health outcomes, and institutionalization, and other changes in living arrangements, as well as changes in life situations and quality of life issues. During this 7th Wave (dataset 1), 2010-2011, re-interviews were conducted either in person or by proxy, with 659 of the original respondents. This Wave also includes 419 re-interviews from the additional sample of Mexican Americans aged 75 years and over with higher average-levels of education than those of the surviving cohort who were added in Wave 5, increasing the total number of respondents to 1,078. The Wave 7 Informant Interviews dataset (dataset 2) includes data which corresponds to the sixth follow-up of the baseline Hispanic EPESE Wave 7 and included re-interviews with 1,078 Mexican Americans aged 80 years and older. During these interviews, participants were asked to provide the name and contact information of the person they are "closer to" or they "depend on the most for help." These INFORMANTS were contacted and interviewed regarding the health, function, social situation, finances, and general well-being of the ongoing Hispanic EPESE respondents. Information was also collected on the informant's health, function, and caregiver responsibilities and burden. This dataset includes information from 925 informants, more than two-thirds of whom were children of the respective respondents.

Comprehensive demographic dataset for Weatherford, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Abstract (en): This data collection contains extracts of the original DUALabs Special Fifth Count ED/BG Summary Tapes. They are comprised of limited demographic and socioeconomic variables for 27 states in the continental United States. Data are provided at the county, minor civil division, enumeration district, and block group levels for total population and Spanish heritage population for the following states: Minnesota, Nevada, Wyoming, Indiana, Kansas, Nebraska, Oklahoma, South Dakota, Colorado, Arizona, Utah, North Dakota, Montana, Idaho, Missouri, Washington, Iowa, Louisiana, Arkansas, Ohio, Michigan, Wisconsin, Illinois, Oregon, Texas, New Mexico, and California. Demographic variables provide information on race, age, sex, country and place of origin, income, and family status and size. The data were obtained by ICPSR from the National Chicano Research Network, Survey Research Center, Institute for Social Research, University of Michigan. 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: Created variable labels and/or value labels.. A total of 27 states in the continental United States. 2011-08-18 SAS, SPSS, and Stata setups have been added to this data collection.2006-01-12 All files were removed from dataset 28 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 28 and flagged as study-level files, so that they will accompany all downloads.

Comprehensive demographic dataset for Stephenville, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Taxonomy, genetics and biogeography each make key contributions to biological conservation. However, integrating these disciplines to obtain a coherent account of the status of a taxon of concern is not always straightforward. This is the case for the cross-border endemic plant Physaria thamnophila (Brassicaceae). This US federally-listed endangered species is restricted to a set of unique geological sites just north of the Rio Grande (Rio Bravo del Norte) river in south Texas, USA. A single highly-disjunct occurrence of this species is found on a geologically and ecologically distinct site 260 km to the south, in Tamaulipas, Mexico. In this work, we quantify the genetic differentiation between the U.S. and Mexican populations using four microsatellite markers and sequences from three nuclear genes. In both sets of data, we find a high level of genetic divergence consistent with geographic isolation on a time scale of 1–2.5 million years. Further, we provide a hypothesis for the geologi..., Plant collections and DNA sampling.—All Physaria species were formerly included in the genus Lesquerella (Al-Shebaz & O’Kane 2002). Tissues were obtained from 1) laboratory-germinated seedlings, 2) herbaria specimens as listed in Appendix 1. Additional tissue collections were made from P. thamnophila populations under permit and consultation with the US Fish and Wildlife Service. We sampled all known populations of P. thamnophila in which plants were present at the time of sampling. Four populations were in Zapata County, Texas, ten in Starr County, Texas, and one in Tamaulipast, Mexico. Approximately 0.5 cm2 of tissue was used for each DNA isolation. DNAs were isolated from both fresh and dried tissue by a simple micro-scale preparation described previously (Pepper & Norwood, 2001). Microsatellite marker analyses.—Genomic DNAs from a single individual from the P. thamnophila SMR population (Starr County, Texas, U.S.A.) were used for microsatellite discovery. DNA fragments cont..., Microsoft Excel GeneAlEx ver. 6.5 (Peakall & Smouse 2012), plug-in for Microsoft Excel., # Physaria thamnophila microsatellite dataset

https://doi.org/10.5061/dryad.4b8gththr

Description of the data and file structure

This .csv file is formatted in GENALEX file format. All details on this data format can be found in this publication:

Peakall, R. and Smouse P.E. (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6, 288-295.

To use this data, import the .csv file into Microsoft Excel and open using the GENLEX Excel plug-in as described in the cited publication. Can then be converted to many other population genetic dataset formats using GENALEX (e.g. GenePop, GenoDive, Arlequin, Structure, SPAGeDI, etc).

Numerical data for allele sizes refers to total fragment size.

Physaria thamnophila is a US federally-listed endangered species. Some samples were collected based on one-time permission from private land-owners. Information on population geographic l...

Comprehensive demographic dataset for Arlington, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.