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Context
The dataset tabulates the population of White Earth by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for White Earth. The dataset can be utilized to understand the population distribution of White Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in White Earth. 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 White Earth.
Key observations
Largest age group (population): Male # 10-14 years (17) | Female # 40-44 years (13). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
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
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 White Earth Population by Gender. You can refer the same here
Over the past 23 years, there were constantly more men than women living on the planet. Of the 8.06 billion people living on the Earth in 2023, 4.05 billion were men and 4.01 billion were women. One-quarter of the world's total population in 2024 was below 15 years.
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 International Falls by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for International Falls. The dataset can be utilized to understand the population distribution of International Falls by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in International Falls. 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 International Falls.
Key observations
Largest age group (population): Male # 65-69 years (337) | Female # 40-44 years (306). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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
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 International Falls Population by Gender. You can refer the same here
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 Earth by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Earth. The dataset can be utilized to understand the population distribution of Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Earth. 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 Earth.
Key observations
Largest age group (population): Male # 65-69 years (51) | Female # 10-14 years (76). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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
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 Earth Population by Gender. You can refer the same here
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License information was derived automatically
Context
The dataset tabulates the population of Blue Earth County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Blue Earth County. The dataset can be utilized to understand the population distribution of Blue Earth County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Blue Earth County. 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 Blue Earth County.
Key observations
Largest age group (population): Male # 20-24 years (5,400) | Female # 20-24 years (5,130). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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
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 Blue Earth County Population by Gender. You can refer the same here
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Computed prospective ages for 1950-2100 for all countries and regions based on 2017 Revision of the UN World Population Prospects.Content:1. codebook.pdf contains a brief overview of the dataset, its background and a description of the cases and variables.2. methods.pdf is a (draft but complete) write up of the calculations used to create the dataset.3. 2017_prospective-ages.csv is the human readable form of the prospective age dataset containing the calculated prospective old-age thresholds for 241 countries and regions, for the period 1950-2100, for men, women and both together, as well as the proportions of the population (male, female and total) over these thresholds.This figshare fileset is published directly from the github repository ProspectiveAgeData. For an application of this data see the factsheet on ageing in the Middle East and Northern Africa which will be published in Population Horizons journal.
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Cameroon CM: Population: as % of Total: Female: Aged 15-64 data was reported at 55.623 % in 2023. This records an increase from the previous number of 55.324 % for 2022. Cameroon CM: Population: as % of Total: Female: Aged 15-64 data is updated yearly, averaging 53.039 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 56.935 % in 1960 and a record low of 50.423 % in 1991. Cameroon CM: Population: as % of Total: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cameroon – Table CM.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 15 to 64 as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.;United Nations Population Division. World Population Prospects: 2024 Revision.;Weighted average;Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.
Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.
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Global population data, including fertility rate, gender parity in school enrolment, information on sexual and reproductive health, and much more. Together, these data shine a light on the health and rights of people around the world, especially women and young people. The numbers here come from UNFPA and fellow UN agencies, and are updated annually.
Full report and dashboard available here: https://www.unfpa.org/swop-2019
Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.
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The Demographic and Health Surveys (DHS) Program exists to advance the global understanding of health and population trends in developing countries.
The UN describes violence against women and girls (VAWG) as: “One of the most widespread, persistent, and devastating human rights violations in our world today. It remains largely unreported due to the impunity, silence, stigma, and shame surrounding it.”
In general terms, it manifests itself in physical, sexual, and psychological forms, encompassing: • intimate partner violence (battering, psychological abuse, marital rape, femicide) • sexual violence and harassment (rape, forced sexual acts, unwanted sexual advances, child sexual abuse, forced marriage, street harassment, stalking, cyber-harassment), human trafficking (slavery, sexual exploitation) • female genital mutilation • child marriage
The data was taken from a survey of men and women in African, Asian, and South American countries, exploring the attitudes and perceived justifications given for committing acts of violence against women. The data also explores different sociodemographic groups that the respondents belong to, including: Education Level, Marital status, Employment, and Age group.
It is, therefore, critical that the countries where these views are widespread, prioritize public awareness campaigns, and access to education for women and girls, to communicate that violence against women and girls is never acceptable or justifiable.
Field | Definition |
---|---|
Record ID | Numeric value unique to each question by country |
Country | Country in which the survey was conducted |
Gender | Whether the respondents were Male or Female |
Demographics Question | Refers to the different types of demographic groupings used to segment respondents – marital status, education level, employment status, residence type, or age |
Demographics Response | Refers to demographic segment into which the respondent falls (e.g. the age groupings are split into 15-24, 25-34, and 35-49) |
Survey Year | Year in which the Demographic and Health Survey (DHS) took place. “DHS surveys are nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health and nutrition. Standard DHS Surveys have large sample sizes (usually between 5,000 and 30,000 households) and typically are conducted around every 5 years, to allow comparisons over time.” |
Value | % of people surveyed in the relevant group who agree with the question (e.g. the percentage of women aged 15-24 in Afghanistan who agree that a husband is justified in hitting or beating his wife if she burns the food) |
Question | Respondents were asked if they agreed with the following statements: - A husband is justified in hitting or beating his wife if she burns the food - A husband is justified in hitting or beating his wife if she argues with him - A husband is justified in hitting or beating his wife if she goes out without telling him - A husband is justified in hitting or beating his wife if she neglects the children - A husband is justified in hitting or beating his wife if she refuses to have sex with him - A husband is justified in hitting or beating his wife for at least one specific reason
More - Find More Exciting🙀 Datasets Here - An Upvote👍 A Dayᕙ(`▿´)ᕗ , Keeps Aman Hurray Hurray..... ٩(˘◡˘)۶Haha
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Estonia EE: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.060 Ratio in 2017. This records an increase from the previous number of 1.058 Ratio for 2016. Estonia EE: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.058 Ratio from Dec 1962 (Median) to 2017, with 21 observations. The data reached an all-time high of 1.068 Ratio in 1962 and a record low of 1.052 Ratio in 2012. Estonia EE: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Estonia – Table EE.World Bank.WDI: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;
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Mexico MX: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.050 Ratio in 2017. This stayed constant from the previous number of 1.050 Ratio for 2016. Mexico MX: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.050 Ratio from Dec 1962 (Median) to 2017, with 21 observations. The data reached an all-time high of 1.050 Ratio in 2017 and a record low of 1.050 Ratio in 2017. Mexico MX: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the population of Globe by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Globe. The dataset can be utilized to understand the population distribution of Globe by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Globe. 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 Globe.
Key observations
Largest age group (population): Male # 40-44 years (386) | Female # 50-54 years (413). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
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
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 Globe Population by Gender. You can refer the same here
Women and girls make up more than half the world’s population, but they are also more deeply impacted than men and boys by poverty, violence, discrimination, and economic crises. This inequality holds us all back. Each and every one of the UN's Global Goals for Sustainable Development sets out to address this inequality in some way. Check out this Cascade story map to see some of the issues we face and what the future could look like if we achieve these Goals (click here for more information on the maps, graphics, and data behind the story map).We created this layer using datasets from the World Bank.
The Armenia Demographic and Health Survey (ADHS) was a nationally representative sample survey designed to provide information on population and health issues in Armenia. The primary goal of the survey was to develop a single integrated set of demographic and health data, the first such data set pertaining to the population of the Republic of Armenia. In addition to integrating measures of reproductive, child, and adult health, another feature of the DHS survey is that the majority of data are presented at the marz level.
The ADHS was conducted by the National Statistical Service and the Ministry of Health of the Republic of Armenia during October through December 2000. ORC Macro provided technical support for the survey through the MEASURE DHS+ project. MEASURE DHS+ is a worldwide project, sponsored by the USAID, with a mandate to assist countries in obtaining information on key population and health indicators. USAID/Armenia provided funding for the survey. The United Nations Children’s Fund (UNICEF)/Armenia provided support through the donation of equipment.
The ADHS collected national- and regional-level data on fertility and contraceptive use, maternal and child health, adult health, and AIDS and other sexually transmitted diseases. The survey obtained detailed information on these issues from women of reproductive age and, on certain topics, from men as well. Data are presented by marz wherever sample size permits.
The ADHS results are intended to provide the information needed to evaluate existing social programs and to design new strategies for improving the health of and health services for the people of Armenia. The ADHS also contributes to the growing international database on demographic and health-related variables.
National
Sample survey data
The sample was designed to provide estimates of most survey indicators (including fertility, abortion, and contraceptive prevalence) for Yerevan and each of the other ten administrative regions (marzes). The design also called for estimates of infant and child mortality at the national level for Yerevan and other urban areas and rural areas.
The target sample size of 6,500 completed interviews with women age 15-49 was allocated as follows: 1,500 to Yerevan and 500 to each of the ten marzes. Within each marz, the sample was allocated between urban and rural areas in proportion to the population size. This gave a target sample of approximately 2,300 completed interviews for urban areas exclusive of Yerevan and 2,700 completed interviews for the rural sector. Interviews were completed with 6,430 women. Men age 15-54 were interviewed in every third household; this yielded 1,719 completed interviews.
A two-stage sample was used. In the first stage, 260 areas or primary sampling units (PSUs) were selected with probability proportional to population size (PPS) by systematic selection from a list of areas. The list of areas was the 1996 Data Base of Addresses and Households constructed by the National Statistical Service. Because most selected areas were too large to be directly listed, a separate segmentation operation was conducted prior to household listing. Large selected areas were divided into segments of which two segments were included in the sample. A complete listing of households was then carried out in selected segments as well as selected areas that were not segmented.
The listing of households served as the sampling frame for the selection of households in the second stage of sampling. Within each area, households were selected systematically so as to yield an average of 25 completed interviews with eligible women per area. All women 15-49 who stayed in the sampled households on the night before the interview were eligible for the survey. In each segment, a subsample of one-third of all households was selected for the men's component of the survey. In these households, all men 15-54 who stayed in the household on the previous night were eligible for the survey.
Note: See detailed description of sample design in APPENDIX A of the survey report.
Face-to-face [f2f]
Three questionnaires were used in the ADHS: a Household Questionnaire, a Women’s Questionnaire, and a Men’s Questionnaire. The questionnaires were based on the model survey instruments developed for the MEASURE DHS+ program. The model questionnaires were adapted for use during a series of expert meetings hosted by the Center of Perinatology, Obstetrics, and Gynecology. The questionnaires were developed in English and translated into Armenian and Russian. The questionnaires were pretested in July 2000.
The Household Questionnaire was used to list all usual members of and visitors to a household and to collect information on the physical characteristics of the dwelling unit. The first part of the household questionnaire collected information on the age, sex, residence, educational attainment, and relationship to the household head of each household member or visitor. This information provided basic demographic data for Armenian households. It also was used to identify the women and men who were eligible for the individual interview (i.e., women 15-49 and men 15-54). The second part of the Household Questionnaire consisted of questions on housing characteristics (e.g., the flooring material, the source of water, and the type of toilet facilities) and on ownership of a variety of consumer goods.
The Women’s Questionnaire obtained information on the following topics: - Background characteristics - Pregnancy history - Antenatal, delivery, and postnatal care - Knowledge and use of contraception - Attitudes toward contraception and abortion - Reproductive and adult health - Vaccinations, birth registration, and health of children under age five - Episodes of diarrhea and respiratory illness of children under age five - Breastfeeding and weaning practices - Height and weight of women and children under age five - Hemoglobin measurement of women and children under age five - Marriage and recent sexual activity - Fertility preferences - Knowledge of and attitude toward AIDS and other sexually transmitted infections.
The Men’s Questionnaire focused on the following topics: - Background characteristics - Health - Marriage and recent sexual activity - Attitudes toward and use of condoms - Knowledge of and attitude toward AIDS and other sexually transmitted infections.
After a team had completed interviewing in a cluster, questionnaires were returned promptly to the National Statistical Service in Yerevan for data processing. The office editing staff first checked that questionnaires for all selected households and eligible respondents had been received from the field staff. In addition, a few questions that had not been precoded (e.g., occupation) were coded at this time. Using the ISSA (Integrated System for Survey Analysis) software, a specially trained team of data processing staff entered the questionnaires and edited the resulting data set on microcomputers. The process of office editing and data processing was initiated soon after the beginning of fieldwork and was completed by the end of January 2001.
A total of 6,524 households were selected for the sample, of which 6,150 were occupied at the time of fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. Of the occupied households, 97 percent were successfully interviewed.
In these households, 6,685 women were identified as eligible for the individual interview (i.e., age 15-49). Interviews were completed with 96 percent of them. Of the 1,913 eligible men identified, 90 percent were successfully interviewed. The principal reason for non-response among eligible women and men was the failure to find them at home despite repeated visits to the household. The refusal rate was low.
The overall response rates, the product of the household and the individual response rates, were 94 percent for women and 87 percent for men.
Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the survey report.
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2000 Armenia Demographic and Health Survey (ADHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the ADHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey
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Women roughly occupy half of the world's population but when it comes to the total workforce of a country, the percentage of male and female workers are rarely similar. This is even more prominent for the developing and underdeveloped countries. While several reasons such as the insufficient access to education, religious superstitions, lack of adequate infrastrucutres are responsible for this discrepancy, it goes way beyond these. One significant factor is the fertility rate of women which is a count for the total number of births per an individual woman. And to show its effects on the participation of women in the total workforce, percentage of female workers in the labor force has been considered. Using simple linear regression model, the relationship between these two factors can be analyzed.
The datasets span over 23 years (from 1995 to 2017). Data has been collected separately from two surveys carried out by the World Bank for both the fertility rate and the percentage of female in the total workforce of Bangladesh. These two datasets were compiled into one dataset and it corresponds to the 23 data points for these two variables ("fertility rate" and "worker percent").
Linear model as well as other statistical methods can be applied on this dataset to analyze if there is any viable relationship between these two variables.
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Latvia LV: Population: Female: Ages 35-39: % of Female Population data was reported at 6.067 % in 2017. This records an increase from the previous number of 6.038 % for 2016. Latvia LV: Population: Female: Ages 35-39: % of Female Population data is updated yearly, averaging 6.809 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.295 % in 1963 and a record low of 6.037 % in 2015. Latvia LV: Population: Female: Ages 35-39: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Latvia – Table LV.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 35 to 39 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;
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This dataset contains surveillance study estimates for population size, HIV prevalence, and ART coverage among female sex workers (FSW), men who have sex with men (MSM), people who inject drugs (PWID), and transgender men and women (TGM/W) from 2010-2023. It was created to support the UNAIDS Estimates Key Population Workbook for use by HIV estimates teams in sub-Saharan Africa. Key population surveillance reports, including Ministry of Health-led biobehavioural surveys, mapping studies, and academic studies were used to populate the database.
The dataset was populated using existing key population size estimate databases including:
UNAIDS Key Population Atlas
US Centers for Disease Control and Prevention surveillance database
Global Fund against HIV/AIDS, TB, and Malaria surveillance database
Global.HIV database
Systematic review databases among MSM (Stannah et al, 2019 and Stannah et al., 2023) and PWID (Degenhardt et al., 2023)
and was additionally supplemented by a literature review of peer-reviewed and grey literature sources.
The data can be explored in this web application and the accompanying manuscript can be found here
Statistics Population of Namur - Indicator: Overall population change with distinction between men and women by neighbourhood. Figures collected on 1 January of each year since 1985. This dataset is used on the Portal "Statistics of the 46 districts of Namur", tab Demographic Observatory of the OPENDATA of the municipality of Namur.
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Context
The dataset tabulates the population of White Earth by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for White Earth. The dataset can be utilized to understand the population distribution of White Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in White Earth. 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 White Earth.
Key observations
Largest age group (population): Male # 10-14 years (17) | Female # 40-44 years (13). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
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
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 White Earth Population by Gender. You can refer the same here