This table contains 6 series, with data for years 1970 - 1984 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Principal statistics (2 items: Ratio of finished goods to shipments; Ratio of total inventory owned to shipments); Type of industry (3 items: All manufacturing industries; Non-durable industries; Durable industries).

As of October 2020, there were around 11.8 thousand outpatients aged 80 to 84 years per 100 thousand inhabitants in Japan in a day. At the same time, approximately 11.5 thousand people aged 75 to 79 years per 100 thousand of the population visited outpatient care in one day.

Brazil Dependency Ratio: Elderly: Southeast: São Paulo data was reported at 23.200 NA in 2015. This records an increase from the previous number of 22.300 NA for 2014. Brazil Dependency Ratio: Elderly: Southeast: São Paulo data is updated yearly, averaging 18.500 NA from Sep 2004 (Median) to 2015, with 11 observations. The data reached an all-time high of 23.200 NA in 2015 and a record low of 15.400 NA in 2004. Brazil Dependency Ratio: Elderly: Southeast: São Paulo data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAE008: Dependency Ratio.

Graph and download economic data for Employment-Population Ratio - 16-19 Yrs., White (LNS12300015) from Jan 1954 to Feb 2025 about 16 to 19 years, employment-population ratio, white, household survey, employment, population, and USA.

The ratio of the combined population aged between 0 to 14 years old and the population aged of 65 years and older to the population aged between 15 to 64 years old. This ratio is presented as the number of dependents for every 100 people in the working age population.

The average home in the U.S. sold for several percent below its asking price in December 2022, as a result of the housing market slowing. Just a few months before that, In the second quarter of 2022, the so-called sale-to-list price ratio went above 100. This reflected the high housing demand and the need of prospective home buyers to bid above the asking price. Housing demand - as measured in pending home sales - went up, as mortgage rates were historically low and plummeted once rates were increased.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 5-9 years (105) | Female # 35-39 years (91). 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 Wakefield population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Wakefield is shown in the following column.
• Population (Female): The female population in the Wakefield 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 Wakefield 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 Wakefield Population by Gender. You can refer the same here

Patterson's D, also known as the ABBA-BABA statistic, and related statistics such as the f4-ratio, are commonly used to assess evidence of gene flow between populations or closely related species. Currently available implementations often require custom file formats, implement only small subsets of the available statistics, and are impractical to evaluate all gene flow hypotheses across datasets with many populations or species due to computational inefficiencies. Here we present a new software package Dsuite, an efficient implementation allowing genome scale calculations of the D and f4-ratio statistics across all combinations of tens or hundreds of populations or species directly from a variant call format (VCF) file. Our program also implements statistics suited for application to genomic windows, providing evidence of whether introgression is confined to specific loci and it can also aid in interpretation of a system of f4-ratio results with the use of the 'f-branch' method. Dsuite is available at https://github.com/millanek/Dsuite, is straightforward to use, substantially more computationally efficient than comparable programs, and provides a convenient suite of tools and statistics, including some not previously available in any software package. Thus, Dsuite facilitates the assessment of evidence for gene flow, especially across larger genomic datasets.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 55-59 years (98) | Female # 60-64 years (125). 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 Long Beach population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Long Beach is shown in the following column.
• Population (Female): The female population in the Long Beach 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 Long Beach 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 Long Beach Population by Gender. You can refer the same here

Affordability ratios calculated by dividing house prices for existing dwellings, by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 20-24 years (2,255) | Female # 20-24 years (1,827). 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 Troy population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Troy is shown in the following column.
• Population (Female): The female population in the Troy 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 Troy 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 Troy Population by Gender. You can refer the same here

Jordan JO: Pupil-Teacher Ratio: Primary data was reported at 18.363 % in 2016. This records an increase from the previous number of 16.909 % for 2014. Jordan JO: Pupil-Teacher Ratio: Primary data is updated yearly, averaging 31.787 % from Dec 1971 (Median) to 2016, with 26 observations. The data reached an all-time high of 38.828 % in 1971 and a record low of 16.909 % in 2014. Jordan JO: Pupil-Teacher Ratio: Primary data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jordan – Table JO.World Bank.WDI: Education Statistics. Primary school pupil-teacher ratio is the average number of pupils per teacher in primary school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

About this dataset

Context

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

Key observations

Largest age group (population): Male # 50-54 years (51) | Female # 40-44 years (67). 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 Oran population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Oran is shown in the following column.
• Population (Female): The female population in the Oran 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 Oran 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 Oran Population by Gender. You can refer the same here

India Commercial Banks: Financial Ratio: Credit Deposit data was reported at 79.600 % in 2024. This records an increase from the previous number of 78.200 % for 2023. India Commercial Banks: Financial Ratio: Credit Deposit data is updated yearly, averaging 67.400 % from Mar 1969 (Median) to 2024, with 54 observations. The data reached an all-time high of 79.600 % in 2024 and a record low of 51.600 % in 1994. India Commercial Banks: Financial Ratio: Credit Deposit data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.KBA001: Commercial Banks: Statistics.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 55-59 years (516) | Female # 55-59 years (501). 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 Itasca population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Itasca is shown in the following column.
• Population (Female): The female population in the Itasca 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 Itasca 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 Itasca Population by Gender. You can refer the same here

Number of job vacancies, number of unemployed and unemployment-to-job vacancies ratio by North American Industry Classification (NAICS), last 5 months.

According to British and French shipping records, plantation records from the British colony of Trinidad and the French colony of St Domingue (present-day Haiti), it appears that the gender ratio of slaves from different regions of Africa varied greatly between 1715 and 1813. On average, there were 163 and 179 males for every 100 females across British and French shipping routes respectively; a significant drop can be observed in the average gender ratios between the shipping routes and the respective colonies. Although this was not always the case when the figures are broken down by region of origin, and the difference in the years (particularly in the British data) should not be ignored, this data does reflect the fact that male slaves had a much higher mortality rate during seasoning (i.e. adjusting to slavery and the new climate).

About this dataset

Context

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

Key observations

Largest age group (population): Male # 20-24 years (1,199) | Female # 20-24 years (494). 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 Gunnison population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Gunnison is shown in the following column.
• Population (Female): The female population in the Gunnison 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 Gunnison 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 Gunnison Population by Gender. You can refer the same here

During the period of time from 1994 to 2018, the average liquidity ratio of banks in the United States was 7.3 percent. In 2019, the liquidity ratio rose to 15.3 percent.

In Japan, the population sex ratio has seen slight changes over the past decades. In 2021, the number of men was around 94.6 for every 100 women, constituting a decrease from 96.1 in 1950.

What is the sex ratio? The population sex ratio is determined by the sex ratio at birth, different mortality rates between men and women, as well as losses and gains through migration. In the absence of alteration, the sex ratio in human populations is quite constant, with only minor deviations. While the sex ratio at birth is usually 105 to 107, the population sex ratio, which refers to the total number of males for every 100 females, is often below 100. The reason for the shift mostly lies in differing lifestyles and physical constitutions of men and women. In general, women tend to be more resistant to disease throughout life, while men tend to engage in higher risk behavior or violence.

Influences and consequences
The sex ratio at birth and its possible determinants such as gestation environment, climate change, chemical pollution or socio-economic factors have long been subject to scientific research. Recently the impact of natural disasters, like the nuclear disaster in Japan in 2011, was presumed to influence the sex ratio at birth. The adult gender ratio has long been recognized as a key population-level determinant of behavior. However, there are many different or competing theories in existing literature about the social impacts of gender imbalance on topics such as violence, family stability, reproduction etc.