Demographic data are important to wildlife managers to gauge population health, to allow populations to be utilised sustainably, and to inform conservation efforts. We analysed published demographic data on the world’s wildfowl to examine taxonomic and geographic biases in study, and to identify gaps in knowledge. Wildfowl (order: Anseriformes) are a comparatively well studied bird group which includes 169 species of duck, goose and swan. In all, 1,586 wildfowl research papers published between 1911 and 2010 were found using Web of Knowledge (WoK) and Google Scholar. Over half of the research output involved just 15 species from seven genera. Research output was strongly biased towards ‘high income’ countries, common wildfowl species, and measures of productivity, rather than survival and movement patterns. There were significantly fewer demographic data for the world’s 31 threatened wildfowl species than for non-threatened species. Since 1994, the volume of demographic work on threatened species has increased more than for non-threatened species, but still makes up only 2.7% of total research output. As an aid to research prioritisation, a metric was created to reflect demographic knowledge gaps for each species related to research output for the species, its threat status, and availability of potentially useful surrogate data from congeneric species. According to the metric, the 25 highest priority species include thirteen threatened taxa and nine species each from Asia and South America, and six from Africa.

Abstract

The Thai Demographic and Health Survey (TDHS) was a nationally representative sample survey conducted from March through June 1988 to collect data on fertility, family planning, and child and maternal health. A total of 9,045 households and 6,775 ever-married women aged 15 to 49 were interviewed. Thai Demographic and Health Survey (TDHS) is carried out by the Institute of Population Studies (IPS) of Chulalongkorn University with the financial support from USAID through the Institute for Resource Development (IRD) at Westinghouse. The Institute of Population Studies was responsible for the overall implementation of the survey including sample design, preparation of field work, data collection and processing, and analysis of data. IPS has made available its personnel and office facilities to the project throughout the project duration. It serves as the headquarters for the survey.

The Thai Demographic and Health Survey (TDHS) was undertaken for the main purpose of providing data concerning fertility, family planning and maternal and child health to program managers and policy makers to facilitate their evaluation and planning of programs, and to population and health researchers to assist in their efforts to document and analyze the demographic and health situation. It is intended to provide information both on topics for which comparable data is not available from previous nationally representative surveys as well as to update trends with respect to a number of indicators available from previous surveys, in particular the Longitudinal Study of Social Economic and Demographic Change in 1969-73, the Survey of Fertility in Thailand in 1975, the National Survey of Family Planning Practices, Fertility and Mortality in 1979, and the three Contraceptive Prevalence Surveys in 1978/79, 1981 and 1984.

Geographic coverage

National

Analysis unit

• Household
• Women age 15-49

Universe

The population covered by the 1987 THADHS is defined as the universe of all women Ever-married women in the reproductive ages (i.e., women 15-49). This covered women in private households on the basis of a de facto coverage definition. Visitors and usual residents who were in the household the night before the first visit or before any subsequent visit during the few days the interviewing team was in the area were eligible. Excluded were the small number of married women aged under 15 and women not present in private households.

Kind of data

Sample survey data

Sampling procedure

SAMPLE SIZE AND ALLOCATION

The objective of the survey was to provide reliable estimates for major domains of the country. This consisted of two overlapping sets of reporting domains: (a) Five regions of the country namely Bangkok, north, northeast, central region (excluding Bangkok), and south; (b) Bangkok versus all provincial urban and all rural areas of the country. These requirements could be met by defining six non-overlapping sampling domains (Bangkok, provincial urban, and rural areas of each of the remaining 4 regions), and allocating approximately equal sample sizes to them. On the basis of past experience, available budget and overall reporting requirement, the target sample size was fixed at 7,000 interviews of ever-married women aged 15-49, expected to be found in around 9,000 households. Table A.I shows the actual number of households as well as eligible women selected and interviewed, by sampling domain (see Table i.I for reporting domains).

THE FRAME AND SAMPLE SELECTION

The frame for selecting the sample for urban areas, was provided by the National Statistical Office of Thailand and by the Ministry of the Interior for rural areas. It consisted of information on population size of various levels of administrative and census units, down to blocks in urban areas and villages in rural areas. The frame also included adequate maps and descriptions to identify these units. The extent to which the data were up-to-date as well as the quality of the data varied somewhat in different parts of the frame. Basically, the multi-stage stratified sampling design involved the following procedure. A specified number of sample areas were selected systematically from geographically/administratively ordered lists with probabilities proportional to the best available measure of size (PPS). Within selected areas (blocks or villages) new lists of households were prepared and systematic samples of households were selected. In principle, the sampling interval for the selection of households from lists was determined so as to yield a self weighting sample of households within each domain. However, in the absence of good measures of population size for all areas, these sampling intervals often required adjustments in the interest of controlling the size of the resulting sample. Variations in selection probabilities introduced due to such adjustment, where required, were compensated for by appropriate weighting of sample cases at the tabulation stage.

SAMPLE OUTCOME

The final sample of households was selected from lists prepared in the sample areas. The time interval between household listing and enumeration was generally very short, except to some extent in Bangkok where the listing itself took more time. In principle, the units of listing were the same as the ultimate units of sampling, namely households. However in a small proportion of cases, the former differed from the latter in several respects, identified at the stage of final enumeration: a) Some units listed actually contained more than one household each b) Some units were "blanks", that is, were demolished or not found to contain any eligible households at the time of enumeration. c) Some units were doubtful cases in as much as the household was reported as "not found" by the interviewer, but may in fact have existed.

Mode of data collection

Face-to-face

Research instrument

The DHS core questionnaires (Household, Eligible Women Respondent, and Community) were translated into Thai. A number of modifications were made largely to adapt them for use with an ever- married woman sample and to add a number of questions in areas that are of special interest to the Thai investigators but which were not covered in the standard core. Examples of such modifications included adding marital status and educational attainment to the household schedule, elaboration on questions in the individual questionnaire on educational attainment to take account of changes in the educational system during recent years, elaboration on questions on postnuptial residence, and adaptation of the questionnaire to take into account that only ever-married women are being interviewed rather than all women. More generally, attention was given to the wording of questions in Thai to ensure that the intent of the original English-language version was preserved.

a) Household questionnaire

The household questionnaire was used to list every member of the household who usually lives in the household and as well as visitors who slept in the household the night before the interviewer's visit. Information contained in the household questionnaire are age, sex, marital status, and education for each member (the last two items were asked only to members aged 13 and over). The head of the household or the spouse of the head of the household was the preferred respondent for the household questionnaire. However, if neither was available for interview, any adult member of the household was accepted as the respondent. Information from the household questionnaire was used to identify eligible women for the individual interview. To be eligible, a respondent had to be an ever-married woman aged 15-49 years old who had slept in the household 'the previous night'.

Prior evidence has indicated that when asked about current age, Thais are as likely to report age at next birthday as age at last birthday (the usual demographic definition of age). Since the birth date of each household number was not asked in the household questionnaire, it was not possible to calculate age at last birthday from the birthdate. Therefore a special procedure was followed to ensure that eligible women just under the higher boundary for eligible ages (i.e. 49 years old) were not mistakenly excluded from the eligible woman sample because of an overstated age. Ever-married women whose reported age was between 50-52 years old and who slept in the household the night before birthdate of the woman, it was discovered that these women (or any others being interviewed) were not actually within the eligible age range of 15-49, the interview was terminated and the case disqualified. This attempt recovered 69 eligible women who otherwise would have been missed because their reported age was over 50 years old or over.

b) Individual questionnaire

The questionnaire administered to eligible women was based on the DHS Model A Questionnaire for high contraceptive prevalence countries. The individual questionnaire has 8 sections: - Respondent's background - Reproduction - Contraception - Health and breastfeeding - Marriage - Fertility preference - Husband's background and woman's work - Heights and weights of children and mothers

The questionnaire was modified to suit the Thai context. As noted above, several questions were added to the standard DHS core questionnaire not only to meet the interest of IPS researchers hut also because of their relevance to the current demographic situation in Thailand. The supplemental questions are marked with an asterisk in the individual questionnaire. Questions concerning the following items were added in the individual questionnaire: - Did the respondent ever

Demographic characteristics of study population.

The American black bear (Ursus americanus) has one of the broadest geographic distributions of any mammalian carnivore in North America. Populations occur from high to low elevations and from mesic to arid environments, and their demographic traits have been documented in a wide variety of environments. However, the demography of American black bears in semiarid environments, which comprise a significant portion of the geographic range, is poorly documented. To fill this gap in understanding, we used data from a long-term mark-recapture study of black bears in the semiarid environment of eastern Utah, USA. Cub and yearling survival were low and adult survival was high relative to other populations. Adult life stages had the highest reproductive value, comprised the largest proportion of the population, and exhibited the highest elasticity contribution to the population growth rate (i.e., λ). Vital rates of black bears in this semiarid environment are skewed toward higher survival of adu..., Mark-Recapture study We estimated survival rates from long-term mark-recapture data gathered as part of a 27-year study on American black bears of the East Tavaputs Plateau. During the first 12 years of the study (June to August 1991-2003) female bears were captured and radio-collared, and all bears were tagged in the ear, except for cubs and yearlings. For the entire study (1992 – 2019), collared females were visited in their dens annually during their winter hibernation to count newborn cubs and surviving yearlings. Age of individual bears was determined by 2 methods: (1) direct observation of cubs or yearlings (i.e., year of birth was known) or (2) cementum annuli analysis of a cross-section of the root of an extracted premolar (Palochak, 2004; Willey, 1974). The data we used to derive survival and fecundity rates consisted of the ID_number, cohort (cub, yearling, subadult, prime-aged adult, and old adult), age in years, sex (female, male, unknown), number of cubs, number of yearling..., , # Demography of American black bears (Ursus americanus) in a semiarid environment

https://doi.org/10.5061/dryad.98sf7m0t8

Description of the data and file structure

Files and variables

File: Age-Specific_Survivorship.csv

Description:Â

This CSV file contains data collected from a mark-recapture study during 1991 - 2019. We calculated the age-specific average survival rate for each cohort. The average survival rate of each cohort was later used in the matrix transition model as matrix elements to retrieve important demographic information about this population of North American black bears (Ursus americanus) found in a semiarid environment.Â

Variables

• Cohort:Â Yearling = 1 year to 2 years;Â Subadult = 2 years to 4 years;Â Prime-aged Adult = 4 years to 14 years;Â Old Adult = 15 years and older.
• Sex:Â M = male; F = female; U = unknown
• Cubs and Yearlings:Â NV = not visited; number = number of cubs or yearlings presen...

This project was designed to investigate the response of plant growth and reproduction to short- and long-term variation in biotic and abiotic environmental variables. Several perennial taxa, including tree (Juniperus monsperma and Pinus edulis), shrub (Larrea tridentata) and bunch grasses (Oryzopsis hymenoides (now Achnaterum hymenoides) and Sporobolus contractus) species, were monitored at 1-3 sites differing in elevation and topography as well as edaphic variables and annual precipitation. The sites represented optimal or marginal/transitional zones for particular species. Demographic measurements were made biannually, after the 'wet' (fall) and 'dry' (spring) seasons. For tree and shrub species, estimates of growth and reproduction were based on branch demography, with ten branch tips from 10-20 individuals per species per site repeatedly measured from 1989-1993. For J. monsperma, P. edulis and L. tridentata, vegetative growth (i.e., branch growth) as well as reproduction were monitored. Additional measurements included needle length for P. edulis and leaf production, leaf size and branchlet production for L. tridentata. For grasses, basal diameter, leaf length and reproduction were monitored for 100 individuals per species per site.This project, SEV006, contains only data on pinon branch demography. Data on other variables and species is contained in SEV024, SEV025, SEV026, SEV027, and SEV028.

Medical Service Study Areas (MSSAs)As defined by California's Office of Statewide Health Planning and Development (OSHPD) in 2013, "MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data" (Source). Each census tract in CA is assigned to a given MSSA. The most recent MSSA dataset (2014) was used. Spatial data are available via OSHPD at the California Open Data Portal. This information may be useful in studying health equity.Definitions:Race/Ethnicity: Race/ethnicity is categorized as: All races/ethnicities, Non-Hispanic (NH) White, NH Black, Asian/Pacific Islander, or Hispanic. "All races" includes all of the above, as well as other and unknown race/ethnicity and American Indian/Alaska Native. The latter two groups are not reported separately due to small numbers for many cancer sites.Racial/Ethnic Composition: Distribution of residents' race/ethnicity (e.g., % Hispanic, % non-Hispanic White, % non-Hispanic Black, % non-Hispanic Asian/Pacific Islander). (Source: US Census, 2010.)Rural: Percent of residents who reside in blocks that are designated as rural. (Source: US Census, 2010.)Foreign Born: Percent of residents who were born outside the United States. (Source: American Community Survey, 2008-2012.)Socioeconomic Status (Neighborhood Level): A composite measure of seven indicator variables created by principal component analysis; indicators include: education, blue-collar job, unemployment, household income, poverty, rent, and house value. Quintiles based on state distribution, with quintile 1 being the lowest SES and 5 being the highest. (Source: American Community Survey, 2008-2012.)Spatial extent: CaliforniaSpatial Unit: MSSACreated: n/aUpdated: n/aSource: California Health MapsContact Email: gbacr@ucsf.eduSource Link: https://www.californiahealthmaps.org/?areatype=mssa&address=&sex=Both&site=AllSite&race=&year=05yr&overlays=none&choropleth=Obesity

About this dataset

Context

The dataset tabulates the data for the Morgan Hill, CA population pyramid, which represents the Morgan Hill population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Morgan Hill, CA, is 34.1.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Morgan Hill, CA, is 22.2.
• Total dependency ratio for Morgan Hill, CA is 56.3.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Morgan Hill, CA is 4.5.

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

Variables / Data Columns

• Age Group: This column displays the age group for the Morgan Hill population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Morgan Hill for the selected age group is shown in the following column.
• Population (Female): The female population in the Morgan Hill for the selected age group is shown in the following column.
• Total Population: The total population of the Morgan Hill for the selected age group is shown in the following column.

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 Morgan Hill Population by Age. You can refer the same here

This research aimed to analyze the demographic consequences of being refugees for Malian Kel Tamasheq (Tuareg) people by comparing demographic data which were collected in 1981 with new data (included in this dataset) collected in 2001. In 1981, the population were 100% nomadic pastoralists, transhuming in and around the Inner Niger Delta and had an unusual demographic regime for a rural West African population.

From 1991-95 a rebellion in northern Mali forced the majority of high status Tamasheq from this area to flee to refugee camps in Mauritania where some spent up to 5 years. They were repatriated in 1996-97. Many socio-economic and political changes along with the actual experience of being persecuted and forced to flee suggested that the whole process may also have had significant repercussions for demographic behaviour. This study was undertaken to establish in what ways their demography has changed in the intervening twenty years and to examine the contribution of different factors to such change: for example, changing household economy, sedentarisation, disappearance of servile labour force, access to health and education services in the refugee camps, changing political awareness, and changing relationships with other ethnic groups in their areas of origin.

Both quantitative and qualitative data were collected. A single round demographic survey in 2001 – largely covering the same population as in 1981 - provides the base-line quantitative data for analysis of demographic change. An anthropological study, undertaken over 18 months focused on four communities (two nomadic, two sedentary) and peoples' experiences of the rebellion and repatriation period. This component included participant observation, in-depth interviews, life histories and a multi-round survey of 67 households over a year focusing on economic organisation and well-being, livelihood strategies, migrations and movements. These multi-round households included nomadic and sedentary, refugee and non-refugee, high status and low status.

The quantitative data for this study are available as data files, but the interview material has been included in the background documentation. Some of the interview material is in French.

This dataset is about: Sea-bed images of permanent transects of red coral demography study at Marseille, site Riou Sud, transect 060619_RRS_RG_TCP. Quadrat area 400 cm²

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in University Place: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 609(4.49%) households where the householder is under 25 years old, 4,305(31.74%) households with a householder aged between 25 and 44 years, 4,728(34.86%) households with a householder aged between 45 and 64 years, and 3,920(28.90%) households where the householder is over 65 years old.
• In University Place, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for University Place median household income by age. You can refer the same here

This dataset is about: Sea-bed images of permanent transects of red coral demography study at Marseille, site Plane Grotte à Peres, transect 050308_PGP_RG_TCP. Quadrat area 400 cm²

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Ulysses town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 12(0.54%) households where the householder is under 25 years old, 484(21.82%) households with a householder aged between 25 and 44 years, 889(40.08%) households with a householder aged between 45 and 64 years, and 833(37.56%) households where the householder is over 65 years old.
• In Ulysses town, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Ulysses town median household income by age. You can refer the same here

Selection for higher education (HE) programs may hinder equal opportunities for applicants and thereby reduce student diversity and representativeness. However, variables which could play a role in inequality of opportunity are often studied separately from each other. Therefore, this retrospective cohort study conducts an innovative intersectional analysis of the inequality of opportunity in admissions to selective HE programs. Using a combination of multivariable logistic regression analyses and descriptive statistics, we aimed to investigate 1) the representativeness of student populations of selective HE programs, as compared to both the applicant pool and the demographics of the age cohort; 2) the demographic background variables which are associated with an applicant’s odds of admission; and 3) the intersectional acceptance rates of applicants with all, some or none of the background characteristics positively associated with odds of admission. The study focused on all selective HE programs (n = 96) in The Netherlands in 2019 and 2020, using Studielink applicant data (N = 85,839) and Statistics Netherlands microdata of ten background characteristics. The results show that student diversity in selective HE programs is limited, partly due to the widespread inequality of opportunity in the selection procedures, and partly due to self-selection. Out of all ten variables, migration background was most often (negatively) associated with the odds of receiving an offer of admission. The intersectional analyses provide detailed insight into how (dis)advantage has different effects for different groups. We therefore recommend the implementation of equitable admissions procedures which take intersectionality into account.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Whitestown: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 213(5.20%) households where the householder is under 25 years old, 2,255(55.09%) households with a householder aged between 25 and 44 years, 1,184(28.93%) households with a householder aged between 45 and 64 years, and 441(10.77%) households where the householder is over 65 years old.
• In Whitestown, the age group of 25 to 44 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

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

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Whitestown median household income by age. You can refer the same here

Keywords; Search terms: historical time series; historical statistics; histat / HISTAT . Abstract: Investigations on the development of economic and demographic parameters during industrialization according to cities and regions (time series). Topics: Demographic parameters: births, deaths, marriages, infant mortality, child mortality. Economic parameters: rye price, livestock holdings, proportion of those employed in agriculture, degree of urbanization. Factual classification of corresponding data tables:A. Population in PrussiaA.1 Population in Prussia (1748-1816)A.2 Natural demographic movement in Prussia (1748-1805)A.3 Demographic movement in Prussia (1816-1914)A.4 Population and lifestock farming in Prussia (1816-1913)A.5 Population of the Prussian administrative districts (1816-1883) B. Population in the administrative district of HagenB.1 Demographic development in the administrative district of Hagen (1817-1910)B.2 Demographic development of Hagen according to different classification figures (1818-1867)B.3 Growth rates of the population, migration, and density of population in the administrative district of Hagen (1818-1905)B.4 Population growth in cities and rural communities in the administrative district of Hagen (1818-1871) C. The inner regional structure of the natural demographic movement in the administrative district of Hagen C.1 Births in the administrative district of Hagen (1817-1863)C.2 Deaths in the administrative district of Hagen (1817-1863)C.3 Marriages in the administrative district of Hagen (1817-1863)C.4 Marital fertility in the administrative district of Hagen (1818-1863)C.5 Rate of illegitimate children in the administrative district of Hagen (1817-1863) D. Mortality in the administrative district of HagenD.1 Child mortality in the administrative district of Hagen (1817-1863)D.2 Infant mortality in the administrative district of Hagen (1817-1863)D.3 Age structure of child mortality in the administrative district of Hagen (1817-1863)D.4 Age structure of adolescent and adult mortality in the administrative district of Hagen (1817-1863)D.5 Child and infant mortality in the administrative district of Hagen (1818-1863)D.6 Child mortality (up to 14 years) in the administrative district of Hagen (1817-1863)D.7 Infant mortality (up to one year) in the administrative district of Hagen (1817-1863)D.8 Infant mortality (up to one year) in the administrative district of Hagen (1817-1863)D.9 Stillborn children in the administrative district of Hagen (1817-1863)

The study explores university students' perceptions of e-learning in the context of the ongoing COVID-19 epidemic. The study finds that students prefer e-learning because it enables them to connect with their lecturers and fellow students and engage with their study materials at their leisure, and with the freedom to choose their preferred location and time. One of the key reason students choose e-learning is the ease with which they may obtain study resources. The research methods used with a quantitative model, where the sample tested represented the student of 1137 respondents from 43 universities in Indonesia. The study's findings show the weakness of e-learning is that the majority of respondents responded in turn to interaction with lecturers (52,7%). The study also identified that the majority of respondents have a moderate mastery of technology, 1038 individuals (77.6%), while the remainder has poor knowledge of technology, as many as 52 people (3.9%). According to the study, e-learning technology enables quick access to information, which results in students developing a favorable attitude toward it based on its utility, self-efficacy, the convenience of use, and student behavior related to e-learning. The study verifies the utility of e-learning by demonstrating how it enables students to study from any geographical location, which is not achievable with face-to-face instruction.

Feature Service generated from running the Aggregate Points solutions. Points from Facebook Likes and Shares were aggregated to Study Area Municipalities (with demographics)

There are more male LinkedIn users than females – although it is pretty balanced.

no abstract provided

About this dataset

Context

The dataset presents the median household income across different racial categories in West Covina. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of West Covina population by race & ethnicity, the population is predominantly Asian. This particular racial category constitutes the majority, accounting for 29.92% of the total residents in West Covina. Notably, the median household income for Asian households is $102,645. Interestingly, Asian is both the largest group and the one with the highest median household income, which stands at $102,645.

https://i.neilsberg.com/ch/west-covina-ca-median-household-income-by-race.jpeg" alt="West Covina median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in West Covina.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

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 West Covina median household income by race. You can refer the same here