Repeaters in Grade 2 of primary education, both sexes (number) in Monaco was reported at 4 Persons in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. Monaco - Repeaters in Grade 2 of primary education, both sexes - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Question Paper Solutions of chapter Descriptive Statistics of Probability and Statistics, 2nd Semester , Master of Computer Applications (2 Years)

In 2022, there were 826 public and 454 private 2-year higher education institutions across the United States. The number of both private and public 2-year institutions has decreased since 2012.

2-year higher education institutions includes universities, colleges, professional schools, and junior and teachers' colleges.

Abstract

In 2010, the EU-SILC instrument covered 32 countries, that is, all EU Member States plus Iceland, Turkey, Norway, Switzerland and Croatia. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labor, education and health observations only apply to persons aged 16 and over. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 6th version of the 2010 Cross-Sectional User Database as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria; Belgium; Bulgaria; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Spain; Ireland; Italy; Latvia; Lithuania; Luxembourg; Hungary; Malta; Netherlands; Poland; Portugal; Romania; Slovenia; Slovakia; Sweden; United Kingdom; Iceland; Norway; Turkey; Switzerland

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

This table contains data from the December release of Canadian Business Counts for 2007 until the latest complete year. The data includes the year, 2-digit North American Industry Classification System (NAICS) code, and a count of the number of businesses by number of employees. The table data shows the number of businesses categorized by the number of employees they have. Please ensure you read the notes provided below, as there is very important information on classification and comparability. NotesStatistics Canada advises users not to use these data as a time series. Further, the counts may reflect some of the business openings and closures caused by the COVID-19 pandemic, although they will not be fully represented as the evolving resumption or permanent closure of businesses may not yet be fully processed and confirmed by Statistics Canada's Business Register (The Daily — Canadian business counts, December 2021 (statcan.gc.ca)).Changes in methodology or in business industrial classification strategies used by Statistics Canada's Business Register can create increases or decreases in the number of active businesses reported in the data on Canadian business patterns. As a result, these data do not represent changes in the business population over time. Statistics Canada recommends users not to use these data as a time series. Beginning in December 2014, there were several important changes that were made:

The data appear in two separate series, one covering locations with employees, the other covering locations without employees. The second series corresponds to locations previously coded to the employment category called "indeterminate." A new North American Industrial Classification System (NAICS) category has been added to include locations that have not yet received a NAICS code: unclassified. It represents an additional 78,718 locations with employees and 313,107 locations without employees. The second series, locations without employees, also includes locations that were not previously included in tables but that meet the criteria used to define the Business Register coverage. The impact of the change will be the inclusion of approximately 600,000 additional locations.

Before 2014, the following notes apply:

The establishments in the "Indeterminate" category do not maintain an employee payroll, but may have a workforce which consists of contracted workers, family members or business owners. However, the Business Register does not have this information available, and has therefore assigned the establishments to an "Indeterminate" category. This category also includes employers who did not have employees in the last 12 months. Please note that the employment size ranges are based on data derived from payroll remittances. As such, it should be viewed solely as a business stratification variable. Its primary purpose is to improve the efficiency of samples selected to conduct statistical surveys. It should not be used in any manner to compile industry employment estimates. Employment, grouped in employment size ranges, is more often than not an estimation of the annual maximum number of employees. For example, a measure of "10 employees" could represent "10 full-time employees", "20 part-time employees" or any other combination.For more information refer to Statistics Canada's Definitions and Concepts used in Business Register.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 40-44 years (2) | Female # 15-19 years (2). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the St. Cloud population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the St. Cloud is shown in the following column.
• Population (Female): The female population in the St. Cloud is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in St. Cloud for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for St. Cloud Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

Largest age group (population): Male # 70-74 years (2) | Female # 65-69 years (2). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Three Creeks population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Three Creeks is shown in the following column.
• Population (Female): The female population in the Three Creeks is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Three Creeks for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Three Creeks Population by Gender. You can refer the same here

United States PDS: Net Positions: TIPS: < 2 years data was reported at 16.386 USD bn in 30 Apr 2025. This records an increase from the previous number of 13.133 USD bn for 23 Apr 2025. United States PDS: Net Positions: TIPS: < 2 years data is updated weekly, averaging 4.701 USD bn from Apr 2013 (Median) to 30 Apr 2025, with 631 observations. The data reached an all-time high of 16.846 USD bn in 15 May 2024 and a record low of -3.564 USD bn in 28 Apr 2021. United States PDS: Net Positions: TIPS: < 2 years data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.Z040: Primary Dealer Statistics: Net Positions.

Question Paper Solutions of Probability and Statistics (MCAN-E205C ),2nd Semester,Master of Computer Applications (2 Years),Maulana Abul Kalam Azad University of Technology

About this dataset

Context

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

Key observations

Largest age group (population): Male # 55-59 years (4) | Female # 50-54 years (2). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the White Pine township population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the White Pine township is shown in the following column.
• Population (Female): The female population in the White Pine township is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in White Pine township for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for White Pine township Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

Largest age group (population): Male # 60-64 years (2) | Female # 0-4 years (0). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Lost Springs population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Lost Springs is shown in the following column.
• Population (Female): The female population in the Lost Springs is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Lost Springs for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Lost Springs Population by Gender. You can refer the same here

Taichung City Deed Tax Collection Statistics-This Year

About this dataset

Context

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

Key observations

Largest age group (population): Male # 70-74 years (5) | Female # 45-49 years (2). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the South Red River township population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the South Red River township is shown in the following column.
• Population (Female): The female population in the South Red River township is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in South Red River township for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for South Red River township Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

Largest age group (population): Male # 60-64 years (3) | Female # 60-64 years (2). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Leal population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Leal is shown in the following column.
• Population (Female): The female population in the Leal is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Leal for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Leal Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

Largest age group (population): Male # 65-69 years (2) | Female # 85+ years (4). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Lonerock population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Lonerock is shown in the following column.
• Population (Female): The female population in the Lonerock is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Lonerock for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Lonerock Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

Largest age group (population): Male # 20-24 years (2) | Female # 55-59 years (4). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the York population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the York is shown in the following column.
• Population (Female): The female population in the York is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in York for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for York Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

Largest age group (population): Male # 50-54 years (5) | Female # 5-9 years (2). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Huntsdale population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Huntsdale is shown in the following column.
• Population (Female): The female population in the Huntsdale is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Huntsdale for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Huntsdale Population by Gender. You can refer the same here

Estimates of various low-flow statistics were computed at 66 ungaged stream locations throughout New Jersey during the 2021 water year using methods in the published reports, 1) Streamflow characteristics and trends in New Jersey, water years 1897-2003 (Watson and others, 2005) and 2) Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey (Colarullo and others, 2018). The estimates are computed as needed for use in water resources permitting, assessment, and management by the New Jersey Department of Environmental Protection. The data release includes the stream name, location, drainage area, method of estimation, lowest annual and winter average flows, and the 75 percent flow duration computed during the 2021 water year. The data are provided in plain text file and ArcGIS shapefile formats. References for publications cited: - Colarullo, S.J., Sullivan, S.L., and McHugh, A.R., 2018, Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey: U.S. Geological Survey Open-File Report 2018-1089, 20 p., accessed March 31, 2022, at https://doi.org/10.3133/ofr20181089. - Watson, K.M., Reiser, R.G., Nieswand, S.P., and Schopp, R.D., 2005, Streamflow characteristics and trends in New Jersey, water years 1897-2003: U.S. Geological Survey Scientific Investigations Report 2005-5105, 131 p., accessed March 31, 2022, at https://doi.org/10.3133/sir20055105.