Third grade English Language Arts (ELA) and Math test results for the 2016-2017 school year by census tract for the state of Michigan. Data Driven Detroit obtained these datasets from MI School Data, for the State of the Detroit Child tool in July 2017. Test results were originally obtained on a school level and aggregated to census tract by Data Driven Detroit. Student data was suppressed when less than five students were tested per school.Click here for metadata (descriptions of the fields).

Compares percent distribution of STEM (science, technology, engineering and math and computer science) and BHASE (non-STEM) fields of study between census divisions.

The Great Britain Historical Database has been assembled as part of the ongoing Great Britain Historical GIS Project. The project aims to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain at sub-county scales. Further information about the project is available on A Vision of Britain webpages, where users can browse the database's documentation system online.

These data were originally collected by the Censuses of Population for England and Wales, and for Scotland. They were computerised by the Great Britain Historical GIS Project and its collaborators. They form part of the Great Britain Historical Database, which contains a wide range of geographically-located statistics, selected to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain, generally at sub-county scales.

The census gathered data on levels of educational attainment only from 1951. In 1951 and 1961, attainment was measured simply by the age at which a person's education was completed, rather than by the level of qualifications achieved. These data cover, broadly, the adult population, including many people who had completed their education decades before the relevant census, so the data are indicative of the general level of education of the workforce at the census date, but are a problematic guide to the performance of the education system at that date. The census reports also include cross-tabulations of age of education completion with current age, but not with the level of geographical detail of the transcribed tables.

The 1951 data for England and Wales were computerised by Danny Dorling (now of Oxford University), as part of research funded by the Joseph Rowntree Foundation.

Latest edition information:

For the 2nd edition (June 2021), data for Scotland for 1951 and data for England & Wales and Scotland for 1961 have been added to the study.

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About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Sterling, Massachusetts, is 26.2.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Sterling, Massachusetts, is 35.5.
• Total dependency ratio for Sterling, Massachusetts is 61.7.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Sterling, Massachusetts is 2.8.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Sterling town Population by Age. You can refer the same here

This dataset uses trajectory data from a large set of drifters to extract and analyze displacement signals associated with coherent eddies in the Gulf of Mexico, using a multivariate wavelet ridge analysis as presented in Lilly and Pérez-Brunius (2021). The data includes eddy displacement signals for all ridges, as well as the time-varying ellipse parameters and estimated ellipse center location. The instantaneous frequency is also included, as is the instantaneous bias estimate derived by Lilly and Olhede (2012). The data are organized as appended trajectory data that can be readily separated through the use of the "ids" field. The ridge length (\(L\)),and ridge-averaged circularity (\(\overline{\xi}\)) are also included, as is measure of statistical significance denoted by (\(\rho\)). The dataset is available for download as a NetCDF file.

Lilly, J. M. and P. Pérez-Brunius (2021). Extracting statistically significant eddy signals from large Lagrangian datasets using wavelet ridge analysis, with application to the Gulf of Mexico. Nonlinear Processes in Geophysics, 28: 181–212. https://doi.org/10.5194/npg-28-181-2021.

Lilly, J. M. and Olhede, S. C.: Analysis of modulated multivariate oscillations, IEEE T. Signal Proces., 60, 600–612, 2012. 10.1109/TSP.2011.2173681

This dataset provides annual population projections for the 50 states and the District of Columbia by age, sex, and race for the years 1986 through 2010. The projections were made using a mathematical projection model called the cohort-component method. This method allows separate assumptions to be made for each of the components of population change: births, deaths, internal migration, and international migration. The projections are consistent with the July 1, 1986 population estimates for states. In general, the projections assume a slight increase in the national levels of fertility, an increasing level of life expectancy, and a decreasing level of net international migration. Internal migration assumptions are based on the annual state-to-state migration data for the years 1975-1986.

Estimated Resident Population (ERP) is the official measure of the Australian population. ERP for sub-state regions (including SA2s and LGAs) is published annually, with a reference date of 30 June. ERP is the official measure of the Australian population, based on the concept of usual residence. It refers to all people, regardless of nationality, citizenship or legal status, who usually live in Australia, with the exception of foreign diplomatic personnel and their families. Note, years 2012-2016 describe preliminary rebased (PR) data. For more information about PR refer to the dataset's Explanatory Notes. This dataset has been compiled using Census data, mathematical models and a range of indicator data. Current indicators include building approvals, Medicare enrolments (provided by the Department of Human Services) and electoral enrolments (provided by the Australian Electoral Commission). Data is sourced from: ABS.Stat and further information is available at http://stat.data.abs.gov.au/Index.aspx?DataSetCode=ABS_ERP_LGA2016. For additional information about this dataset and other related statistics, contact the National Information and Referral Service on 1300 135 070.

Details on STEM (science, technology, engineering and math and computer science) and BHASE (non-STEM) fields of study by highest certificate, diploma or degree, age and gender for census divisions and municipalities.

Mid-year (30 June) estimates of the usual resident population for Lower layer Super Output Areas (LSOAs) in England and Wales by single year of age and sex.

Number and percentage of Indigenous people with a postsecondary credential in STEM (science, technology, engineering and math and computer science) and BHASE (non-STEM) fields of study.

Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

Demographics (2006 and 2011 Census Data) This dataset contains three worksheets. The full description for each column of data is available in the first worksheet called "IndicatorMetaData". The data came from the 2006 and 2011 Census. Some of the data from the 2011 Census was not available at the time of publishing. Refer to the descriptions in worksheet 1 for more information. Users should note that the data for each neighbourhood are based on the mathematical aggregation of smaller sub-areas (in this case Census Tracts) that when combined, define the entire neighbourhood. Since smaller areas may have their values rounded or suppressed (to abide by Statistics Canada privacy standards), the overall total may be undercounted. Population Total (2016 Census Data) The data refers to Total Population from the 2016 Census, aggregated by the City of Toronto to the City's 140 Neighbourhood Planning Areas. Although Statistics Canada makes a great effort to count every person, in each Census a notable number of people are left out for a variety of reasons. For Census 2016: Population and Dwellings example, people may be travelling, some dwellings are hard to find, and some people simply refuse to participate. Statistics Canada takes this into account and for each Census estimates a net 'undercoverage' rate for the urban region, the Toronto Census Metropolitan Area (CMA), but not for the city. The 2011 rate for the Toronto CMA was 3.72% plus or minus 0.53%. The 2016 rate is not yet available

The statistic shows the total population of India from 2019 to 2029. In 2023, the estimated total population in India amounted to approximately 1.43 billion people.

Total population in India

India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population.

With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year.

As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

The statistic shows the total population of South Korea from 2019 to 2023, with projections up until 2029. In 2023, the total population of South Korea was about 51.71 million people. Population of South Korea South Korea, also called Republic of Korea, has one of the highest population densities worldwide, i.e. a very high number of inhabitants per square kilometer. However, this does not equal bad standard of living; on the Human Development Index, which ranks countries by their level of living standards using key factors, such as unemployment rate, literacy rate, fertility and mortality rates, etc., South Korea is among the highest-ranked countries. When looking at the aforementioned key factors, South Korea indeed seems to offer a fairly stable environment for its inhabitants, economically and demographically: The country’s unemployment rate has been relatively steady for the past decade, its gross domestic product (GDP) is constantly increasing, and it is among the countries with the highest trade surplus worldwide. As for standard of living, life expectancy at birth in South Korea is among the highest worldwide – South Korea is even mentioned in a recent ranking of the best birthplaces for children. Despite the high population density, South Korea is now one of the countries with the lowest fertility rates, i.e. the number of babies born by women of childbearing age. This apparent discrepancy could be explained by a high number of immigrants coupled with the aforementioned high life expectancy.

Employment income (in 2019 and 2020) by detailed major field of study and highest certificate, diploma or degree, including work activity (full time full year, part time full year, or part year).