County workforce job data, demographics, and job categories as defined by the Equal Employment Opportunity Commission. More information about the job categories can be found in Appendix 2 at the following link: https://eeocdata.org/EEO4/howto/instructionbooklet

The number of men participating in the labor force in Morocco amounted to around 8.1 million in 2023. The country's labor force predominantly included men. In the same year, only approximately 2.7 million women were part of the labor force, meaning that they were employed or unemployed but actively seeking employment.

Introduction

Employee Feedback Statistics: Employee feedback is when employers or managers give their workers advice or comments on their job performance. It can also mean when workers share their thoughts, ideas, and feelings about the work environment or company policies. Feedback is important because it helps employees know what they are doing well and where they can improve. This process provides employers a chance to understand how workers feel in their roles within any

company. Regular feedback can make employees feel valued and motivated, leading to better performance. Both positive and constructive feedback are necessary for growth and success in the workplace. Creating a culture of open communication encourages teamwork and helps everyone achieve their goals.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Tables for Workplace Geography are only available for States; Counties; Places; County Subdivisions in selected states (CT, ME, MA, MI, MN, NH, NJ, NY, PA, RI, VT, WI); Combined Statistical Areas; Metropolitan and Micropolitan Statistical Areas, and their associated Metropolitan Divisions and Principal Cities. Tables B08601, B08602, B08603, and B08604 are also available for Place parts and County Subdivision parts for the 5-year ACS datasets..These tabulations are produced to provide estimates of workers at the location of their workplace. Estimates of counts of workers at the workplace may differ from those of other programs because of variations in definitions, coverage, methods of collection, reference periods, and estimation procedures. The ACS is a household survey which provides data that pertains to individuals, families, and households..Workers include members of the Armed Forces and civilians who were at work last week..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of e...

According to the 2021 Census, 62.9% (37.5 million) of the overall population of England and Wales was of ‘working age’ (between 16 and 64 years old).

Context

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 infrastructures are responsible for this discrepancy, it goes way beyond these. And to show the effects of multiple socioeconomic factors on the participation of women in the total workforce, percentage of female employment in the total labor force has been considered. Using multiple linear regression model, the relationship between these factors can be analyzed.

Content

For the current study, the data set has been chosen from a survey performed on the population of Bangladesh. The datasets selected for this study span over 25 years (from 1995 to 2019). Data has been collected separately from multiple datasets from the World Bank databank for the employed women percentage and the related predictor variables. These datasets were compiled into one dataset and it corresponds to the 25 data points for the variables. There is one response variable which is the percentage of the employed women and 10 exlnanatory variables of predictors. Brief descriptions of these variables are given below.

PerFemEmploy Employment to population ratio (%) of women who are of age 15 or older. Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.

FertilityRate Fertility rate (birth per women). Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.

RatioMaletoFemale Ratio of female to male labor force participation rate. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.

PerFemEmployers Employers, female (% of female employment). Employers are those workers who, working on their own account or with one or a few partners, hold the type of jobs defined as a "self-employment jobs" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s).

Agriculture Employment in agriculture, female (% of female employment). Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4).

Industry Employment in industry, female (% of female employment). The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).

Services Employment in services, female (% of female employment). The services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4).

Wage.Salaried Wage and salaried workers, female (% of female employment). Wage and salaried workers (employees) are those workers who hold the type of jobs defined as "paid employment jobs," where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.

ContrFamWorkers Contributing family workers, female (% of female employment). Contribut...

While the labor force participation rate of the migrant and non-migrant population was more or less equal in regions such as North Africa, Sub-Saharan Africa, and Latin America and the Caribbean, it was less even in other regions. The largest difference between migrants and non-migrants was found in Arab States, where nearly ** percent of migrants participated in the labor force, meaning that they were either employed or registered as unemployed looking forward. Only ** percent of the local population in Arab States participated in the workforce.

This report shows monthly numbers of NHS Hospital and Community Health Services (HCHS) staff working in NHS Trusts and other core organisations in England (excluding primary care staff). Data are available as headcount and full-time equivalents and for all months from 30 September 2009 onwards. These data are a summary of the validated data extracted from the NHS HR and Payroll system. Additional statistics on staff in NHS Trusts and other core organisations and information for NHS Support Organisations and Central Bodies are published each: September (showing June statistics) December/January (showing September statistics) March (showing December statistics) June (showing March statistics) Quarterly NHS Staff Earnings, monthly NHS Staff Sickness Absence reports, and data relating to the General Practice workforce and the Independent Healthcare Provider workforce are also available via the Related Links below. Please note: We intend ceasing publication of the GPs in alternative settings data file as of next month (May data) meaning April 2023 will be the last issue of these data. Please contact us if you require access to these data on an ongoing basis. We welcome feedback on the methodology and tables within this publication. Please email us with your comments and suggestions, clearly stating Monthly HCHS Workforce as the subject heading, via enquiries@nhsdigital.nhs.uk or 0300 303 5678.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Tables for Workplace Geography are only available for States; Counties; Places; County Subdivisions in selected states (CT, ME, MA, MI, MN, NH, NJ, NY, PA, RI, VT, WI); Combined Statistical Areas; Metropolitan and Micropolitan Statistical Areas, and their associated Metropolitan Divisions and Principal Cities. Tables B08601, B08602, B08603, and B08604 are also available for Place parts and County Subdivision parts for the 5-year ACS datasets..These tabulations are produced to provide estimates of workers at the location of their workplace. Estimates of counts of workers at the workplace may differ from those of other programs because of variations in definitions, coverage, methods of collection, reference periods, and estimation procedures. The ACS is a household survey which provides data that pertains to individuals, families, and households..Workers include members of the Armed Forces and civilians who were at work last week..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of e...

This data collection is comprised of responses from two sets of survey questionnaires, the basic Current Population Survey (CPS) and a survey on the topic of voting and registration in the United States, which was administered as a supplement to the November 2010 CPS questionnaire. The Housing and Household Economic Statistics Division of the Census Bureau sponsored the supplemental questions for November.The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment. Data from the CPS are provided for the week prior to the survey.The voting and registration supplement data are collected every two years to monitor trends in the voting and nonvoting behavior of United States citizens in terms of their different demographic and economic characteristics. The supplement was designed to be a proxy response supplement, meaning a single respondent could provide answers for all eligible household members. The supplement questions were asked of all persons who were both United States citizens and 18 years of age or older. The CPS instrument determined who was eligible for the voting and registration supplement through the use of check items that referred to basic CPS items, including age and citizenship.Respondents were queried on whether they were registered to vote in the November 2, 2010, election, main reasons for not being registered to vote, main reasons for not voting, whether they voted in person or by mail, and method used to register to vote. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income.

In 2025, there were estimated to be approximately 3.6 billion people employed worldwide, compared to 2.23 billion people in 1991 - an increase of around 1.4 billion people. There was a noticeable fall in global employment between 2019 and 2020, when the number of employed people fell from due to the sudden economic shock caused by the COVID-19 pandemic. Formal vs. Informal employment globally Worldwide, there is a large gap between the informally and formally employed. Most informally employed workers reside in the Global South, especially Africa and Southeast Asia. Moreover, men are slightly more likely to be informally employed than women. The majority of informal work, nearly 90 percent, is within the agricultural sector, with domestic work and construction following behind. Women’s employment As the number of employees has risen globally, so has the number of employed women. Overall, care roles such as nursing and midwifery have the highest shares of female employees globally. Moreover, while the gender pay gap has shrunk over time, it still exists. As of 2024, the uncontrolled gender pay gap was 0.83, meaning women made, on average, 83 cents per every dollar earned by men.

This dataset details the number of people working in each municipality by distinguishing them by: - Proximity to the municipality of residence - Sex - Means of transport These results are derived from the complementary exploitation of the 2019 census. Municipal geography as of 1 January 2022. The population census makes it possible to know the diversity and evolution of the population of France. INSEE thus provides statistics on inhabitants and dwellings, their number and characteristics: distribution by sex and age, occupations, housing conditions, modes of transport, commuting, etc. Staff over 500 can normally be used with confidence. Staff below 200 should be handled with caution, as due to the inaccuracy associated with the survey, they may not be significant. Comparisons between territories of small sizes should be prohibited. For areas with less than 2000 inhabitants, it is recommended not to use data from the complementary farm. For more methodological information, you can consult the fact sheets “Tips for the use of census results” by clicking on the link ‘https://www.insee.fr/fr/information/2383177’ These fact sheets present the new features of the population census and discuss their impact on the use of the data. In particular, they specify the changes affecting the main statistical variables and their comparability with previous censuses.

These data are taken from the ANNUAL datasets from the Labour Force Survey (LFS) carried out by the Office for National Statistics (ONS), providing labour market data back to 1996 for the NUTS2 areas in Wales, and back to 2001 for the local authorities in Wales. The availability of local authority data is dependent upon on an enhanced sample (around 350 per cent larger) for the annual LFS, which commenced in 2001. For years labelled 1996 to 2004 in this dataset, the actual periods covered are the 12 months running from March in the year given to February in the following year (e.g. 2001 = 1 March 2001 to 28 February 2002). Since 2004, the annual data have been produced on a rolling annual basis, updated every three months, and the dataset is now referred to as the Annual Population Survey (APS). The rolling annual averages are on a calendar basis with the first rolling annual average presented here covering the period 1 January 2004 to 31 December 2004, followed by data covering the period 1 April 2004 to 31 March 2005, with rolling quarterly updates applied thereafter. Note therefore that the consecutive rolling annual averages overlap by nine months, and there is also a two-month overlap between the last period presented on the former March to February basis, and the first period on the new basis. The population can be broken down into economically active and economically inactive populations. The economically active population is made up of persons in employment, and persons unemployed according to the International Labour Organisation (ILO) definition. This report allows the user to access these data. Although each measure is available for different population bases, there is an official standard population base used for each of the measures, as follows. Population aged 16 and over: Economic activity level, Employment level, ILO unemployment level Population aged 16-64: Economic inactivity level 16-64 population is used as the base for economic inactivity. By excluding persons of pensionable age who are generally retired and therefore economically inactive, this gives a more appropriate measure of workforce inactivity. Rates for each of the above measures are also calculated in a standard manner and are available in the dataset. With the exception of the ILO unemployment rate, each rate is defined in terms of the shares of population that fall into each category. The ILO unemployment rate is defined as ILO unemployed persons as a percentage of the economically active population. Although each rate is available for the different population bases, there is an official standard population base used for each of the rates, as follows. Percentage of population aged 16-64: Economic activity, Employment,. Economic inactivity Percentage of economically active population aged 16 and over: ILO unemployment

In the third quarter of 2024, the employed labor force reached over ** million in Thailand. The total labor force in the country consists of people aged 15 and older who meet the definition of the International Labor Organization of the economically active population.

In this table you will find annual figures on the composition of the Dutch working population according to the international definition. The Dutch definition of the labor force deviates from the definition that applies as an international standard: that of the International Labor Organization (ILO). As a result, the size and composition of the labor force differs. Firstly, the Dutch definition uses a threshold value of twelve hours for the number of hours per week that someone works or wants to work. This is not the case in the international definition. Second, the unemployed labor force is defined differently. According to the international definition, someone should be able to start a job within two weeks. In the Dutch definition, in certain cases, a period of three months is used for the period in which someone can start working or has developed search activities. Data available from 1996/1998 to 2011/2013 Status of the figures Figures based on the EBB are always final. Changes as of February 26, 2015 None, this table has been discontinued. Changes as of April 1, 2014: The figures for 2013 have been added to this table. All data on the profession in 2012 and 2013 are not yet available. As soon as this data becomes available it will be added to this table. The data on the level of education from 2012 onwards are provisional. When will new numbers come out? This table has been discontinued. The update of 1 April 2014 was the last update of this table. On 26 February 2015, new revised tables on the labor force were published. This revision of labor force statistics has two parts. The definitions have been adapted to the internationally agreed definitions and the data collection has been improved by being the first statistics office in Europe to conduct surveys via the internet. For more information on the revision, see the link to the press release in section 3.

Weibo Data Description:Tweets of Weibo during the Spring Festival travel rush, from January 13 to February 21 in 2017 are thoroughly collected to establish the migration network of workforce at the granularity of city.Basic Statistics:Number of cities: 371Number of city pairs(directed): 120,361Number of city pairs(undirected): 61,759Number of all flux: 41,454,268 Data Format:Each line in the file(WorkforceMigrate.csv) demonstrates a 12-tuple (city1,city2,flux,gdp1,gdp2,ave_gdp1,ave_gdp2,population1,population2,geographical_distance,travel_time,travel_distance) defined to denote workforce movement from city1 to city2. Details can be found as follows.1. city1: origin city id2. city2: destination city id3. flux: number of movements from city1 to city24. gdp1: GDP of city15. gdp2: GDP of city26. avg_gdp1: the per capita GDP of city17. avg_gdp2: the per capita GDP of city28. population1: the number of permanent residents in city19. population2: the number of permanent residents in city210. geographical_distance: geographical distance between city1 and city211. travel_distance: travel distance from city1 to city2 provided by Baidu Map API12. travel_time: travel time from city1 to city2 provided by Baidu Map APIData Description:The demographic and economic information in 2015 are collected at the granularity of province.Province Data Format:Each line in file(ProvinceInfo.csv) demonstrates a 8-tuple (province, gdp15, Information Technology Industry,Financial Industry,Real Estate Industry,Scientific Research and Technical Services Industry,income15,R&D) defined to denote the economci information of provinces. Details can be found as follows:1. province: province id2. gdp15: GDP of province3. Information Technology Industry: ratio of practitioner in the information technology industry4. Financial Industry: ratio of practitioner in the Financial industry5. Real Estate Industry: ratio of practitioner in the real estate industry 6. Scientific Research and Technical Services Industry: ratio of practitioner in the scientific research and technical services industry 7. income15: per capita disposable income8. R&D: the fund investment for research and developmentTrain Data Desciption:The national railway line data, including 5,878 trains in total from train schedule are collected to establish the train network at the granularity of city.Basic Statistics:Number of cities: 284 citiesNumber of citi pairs(undirected): 12381Data Format:Each line in the file(Train.csv) demonstrate a triple (city1, city2, train_count) defined to denote trains that pass through city1 and city2. Details can be found as follows:1. city1: city id2. city2: city id3. train_count: the number of trains that pass through city1 and city2Any issues please feel free to contact jichang@buaa.edu.cn.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Tables for Workplace Geography are only available for States; Counties; Places; County Subdivisions in selected states (CT, ME, MA, MI, MN, NH, NJ, NY, PA, RI, VT, WI); Combined Statistical Areas; Metropolitan and Micropolitan Statistical Areas, and their associated Metropolitan Divisions and Principal Cities. Tables B08601, B08602, B08603, and B08604 are also available for Place parts and County Subdivision parts for the 5-year ACS datasets..These tabulations are produced to provide estimates of workers at the location of their workplace. Estimates of counts of workers at the workplace may differ from those of other programs because of variations in definitions, coverage, methods of collection, reference periods, and estimation procedures. The ACS is a household survey which provides data that pertains to individuals, families, and households..Workers include members of the Armed Forces and civilians who were at work last week..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin...

Analysis of ‘Female Employment vs Socioeconimic Factors’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mdmuhtasimbillah/female-employment-vs-socioeconimic-factors on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

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 infrastructures are responsible for this discrepancy, it goes way beyond these. And to show the effects of multiple socioeconomic factors on the participation of women in the total workforce, percentage of female employment in the total labor force has been considered. Using multiple linear regression model, the relationship between these factors can be analyzed.

Content

For the current study, the data set has been chosen from a survey performed on the population of Bangladesh. The datasets selected for this study span over 25 years (from 1995 to 2019). Data has been collected separately from multiple datasets from the World Bank databank for the employed women percentage and the related predictor variables. These datasets were compiled into one dataset and it corresponds to the 25 data points for the variables. There is one response variable which is the percentage of the employed women and 10 exlnanatory variables of predictors. Brief descriptions of these variables are given below.

PerFemEmploy Employment to population ratio (%) of women who are of age 15 or older. Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.

FertilityRate Fertility rate (birth per women). Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.

RatioMaletoFemale Ratio of female to male labor force participation rate. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.

PerFemEmployers Employers, female (% of female employment). Employers are those workers who, working on their own account or with one or a few partners, hold the type of jobs defined as a "self-employment jobs" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s).

Agriculture Employment in agriculture, female (% of female employment). Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4).

Industry Employment in industry, female (% of female employment). The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).

Services Employment in services, female (% of female employment). The services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4).

Wage.Salaried Wage and salaried workers, female (% of female employment). Wage and salaried workers (employees) are those workers who hold the type of jobs defined as "paid employment jobs," where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.

ContrFamWorkers Contributing family workers, female (% of female employment). Contributing family workers are those workers who hold "self-employment jobs" as own-account workers in a market-oriented establishment operated by a related person living in the same household.

OwnAccount Own-account female workers (% of employment). Own-account workers are workers who, working on their own account or with one or more partners, hold the types of jobs defined as "self-employment jobs" and have not engaged on a continuous basis any employees to work for them. Own account workers are a subcategory of "self-employed".

Vulnerable Vulnerable employment, female (% of female employment). Vulnerable employment is contributing family workers and own-account workers as a percentage of total employment.

Inspiration

Linear model as well as other statistical methods can be applied on this dataset to analyze if there is any viable relationship between the predictor and the response variables.

--- Original source retains full ownership of the source dataset ---

Dataset population: Persons aged 16 to 74

Daytime/workday population

England and Wales (Workday Population)

Workday population is where the usually resident population is re-distributed to their places of work, while those not in work are recorded at their usual residence.

The workday population of an area is defined as all usual residents aged 16 and above who are in employment and whose workplace is in the area, and all other usual residents of any age who are not in employment but are resident in the area. People who work mainly at or from home or do not have a fixed place of work are included in their area of their usual residence. The following population groups are excluded from the workday population of an area:

• Those living in England and Wales but working in Scotland, Northern Ireland, outside the UK or on offshore installations,
• Those with a place of work in England and Wales but who are not usually resident in England and Wales, and
• Short-term residents

England and Wales (Workplace Population)

Workplace population is where the usually resident population is re-distributed to their main place of work, but those not working are excluded.

Northern Ireland (Daytime Population)

The daytime population of an area is defined as 'All usual residents who are either in employment or full-time students in the area, or not in employment or full-time students but are usually resident in the area'. People who work or study mainly at or from home, or do not have a fixed place of work or study, are included in the area of their usual residence.

The following population groups are excluded from the daytime population of an area:

• Those living in Northern Ireland but working or studying in England, Wales, Scotland, outside the UK or on offshore installations
• Those with a place of work or study in Northern Ireland but who are not usually resident in Northern Ireland
• Short-term residents

Northern Ireland (Workplace Population)

The workplace population of an area is defined as 'All usual residents aged 16 to 74 who are in employment and whose workplace is in the area'. People who work mainly at or from home or do not have a fixed place of work are included in the area of their usual residence.

The following population groups are excluded from the workplace population of an area:

• Those not working the week before 27 March 2011
• Those living in Northern Ireland but working in England, Wales, Scotland, outside the UK or on offshore installations
• Those with a place of work in Northern Ireland but who are not usually resident in Northern Ireland
• Short-term residents

Economic activity

Economic activity relates to whether or not a person who was aged 16 and over was working or looking for work in the week before census. Rather than a simple indicator of whether or not someone was currently in employment, it provides a measure of whether or not a person was an active participant in the labour market.

A person's economic activity is derived from their 'activity last week'. This is an indicator of their status or availability for employment - whether employed, unemployed, or their status if not employed and not seeking employment. Additional information included in the economic activity classification is also derived from information about the number of hours a person works and their type of employment - whether employed or self-employed.

The census concept of economic activity is compatible with the standard for economic status defined by the International Labour Organisation (ILO). It is one of a number of definitions used internationally to produce accurate and comparable statistics on employment, unemployment and economic status.

United States Private Employee: Defined Benefit Pension (DBP) data was reported at 13.000 % in 2018. This records a decrease from the previous number of 15.000 % for 2017. United States Private Employee: Defined Benefit Pension (DBP) data is updated yearly, averaging 19.000 % from Mar 1999 (Median) to 2018, with 18 observations. The data reached an all-time high of 21.000 % in 2005 and a record low of 13.000 % in 2018. United States Private Employee: Defined Benefit Pension (DBP) data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G077: Employee Benefits Survey: Private Industry.