About this dataset

Context

The dataset tabulates the Science Hill population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Science Hill. The dataset can be utilized to understand the population distribution of Science Hill by age. For example, using this dataset, we can identify the largest age group in Science Hill.

Key observations

The largest age group in Science Hill, KY was for the group of age Under 5 years years with a population of 80 (11.20%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Science Hill, KY was the 85 years and over years with a population of 0 (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

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Science Hill is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Science Hill total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Science Hill Population by Age. You can refer the same here

There is a persistent shortage of underrepresented minority (URM) faculty who are involved in basic biomedical research at medical schools. We examined the entire training pathway of potential candidates to identify the points of greatest loss. Using a range of recent national data sources, including the National Science Foundation’s Survey of Earned Doctorates and Survey of Doctoral Recipients, we analyzed the demographics of the population of interest, specifically those from URM backgrounds with an interest in biomedical sciences. We examined the URM population from high school graduates through undergraduate, graduate, and postdoctoral training as well as the URM population in basic science tenure track faculty positions at medical schools. We find that URM and non-URM trainees are equally likely to transition into doctoral programs, to receive their doctoral degree, and to secure a postdoctoral position. However, the analysis reveals that the diversions from developing a faculty career are found primarily at two clearly identifiable places, specifically during undergraduate education and in transition from postdoctoral fellowship to tenure track faculty in the basic sciences at medical schools. We suggest focusing additional interventions on these two stages along the educational pathway.

About this dataset

Context

The dataset tabulates the Science Hill population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Science Hill across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Science Hill was 652, a 0.15% increase year-by-year from 2022. Previously, in 2022, Science Hill population was 651, a decline of 0.15% compared to a population of 652 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Science Hill decreased by 43. In this period, the peak population was 733 in the year 2008. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Science Hill is shown in this column.
• Year on Year Change: This column displays the change in Science Hill population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Science Hill Population by Year. You can refer the same here

Dataset

This dataset was created by Yussra Elsayed Ibrahim

Contents

About the Dataset

This database presents population and other demographic estimates and projections from 1960 to 2050, covering more than 200 economies. It includes population data by various age groups, sex, urban/rural; fertility data; mortality data; and migration data.

The Graduate Students and Postdoctorates in Science and Engineering survey is an annual census of all U.S. academic institutions granting research-based master's degrees or doctorates in science, engineering, and selected health fields as of fall of the survey year. The survey, sponsored by the National Center for Science and Engineering Statistics within the National Science Foundation and by the National Institutes of Health, collects the total number of master's and doctoral students, postdoctoral appointees, and doctorate-level nonfaculty researchers by demographic and other characteristics such as source of financial support. Results are used to assess shifts in graduate enrollment and postdoc appointments and trends in financial support.

Dataset

This dataset was created by ZhenyuBo

Released under Other (specified in description)

Contents

The U.S. Population Grids (Summary File 1), 2000: Alabama, Louisiana, Mississippi and Texas, Alpha Version data set contains an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

Dataset

This dataset was created by Mpho Mathebula

Contents

The U.S. Census Grids (Summary File 1), 2000 data set contains grids of demographic and socioeconomic data from the year 2000 U.S. Census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

This indicator is no longer maintained, and is considered OBSOLETE.

INDICATOR DEFINITION Demographic parameters for the Adelie penguin at Bechervaise Island near Mawson.

TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system.

This indicator is one of: CONDITION

RATIONALE FOR INDICATOR SELECTION The Adelie penguin is a relatively long lived sea bird dependent on krill. It is expected that major changes in the availability of food (krill) to sea birds will be reflected ultimately in recruitment into the breeding population. Causes of changes in the availability of krill relate directly to changes in both the biological and physical environment brought about by man made or natural means. Ageing populations may give an outward appearance of stability in terms of numbers at a breeding colony but such a condition may mask a decline in recruitment. To determine whether there are environmental influences on the population it is necessary to undertake detailed demographic studies.

Demographic studies carried out over many years on animal populations comprising known age cohorts are required to determine those factors responsible for any observed changes in recruitment and/or mortality. Population reconstruction techniques provide estimates of recruitment and mortality and relate these functions to population size and/or population trends. These studies may alert us to possible changes in the ecosystem particularly related to the availability of food to the penguins or changes to the physical environment. The identification of the cause of changes must come from detailed investigations of food availability and the environment carried out at the same time.

Annual breeding success at Bechervaise Island (eggs laid to chicks fledged) varies enormously from 0 in catastrophic years to above 1 for good seasons. The population at Bechervaise Island near Mawson has been monitored since 1990 as part of the CCAMLR Ecosystem Monitoring Program. Chicks and adults have been tagged annually. The number of breeding pairs has increased slightly between 1990-2001, but changes in the non -breeding population are unknown. Demographic studies based on the return rate of birds tagged as chicks provide information on trends in the overall population and the net rate of recruitment. Since it is intended that this program be undertaken indefinitely it makes this population an excellent subject for monitoring in the context of the SOE.

DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial Scale: Restricted to the Mawson region. Similar studies are carried out by other national research programs at Terra Nova Bay (Italy) and on the Antarctic Peninsula (USA).

Frequency: Annual

Measurement Technique: The Adelie penguin population at Bechervaise Island consists of approximately 1800 breeding pairs. Each breeding season since 1990/91 in excess of 250 chicks have been given implanted electronic identification tags. The return of birds to their natal colony has been detected automatically by the Automated Penguin Monitoring System (APMS)or by checking all birds with a hand held tag reader. Additional and associated biological data as prescribed by CCAMLR (1997 are collected to aid interpretation of demographic and other trends. To detect trends in the population size and in demographic parameters, particularly of recruitment, it will be necessary to maintain an annual tagging program of chicks and recording of all tagged birds.

RESEARCH ISSUES comprehensive analysis of the data collected over the duration of this study is required to determine natural variation and potential anthropogenic influences affecting Adelie penguin population dynamics.

LINKS TO OTHER INDICATORS Sea-ice extent and concentration.

This statistic shows the print and digital reach of New Scientist magazine in Great Britain from January 2015 to December 2015, by demographic group. Reach was higher among men than women, with 787 thousand men reached by the print title or its website monthly.

Overview This dataset re-shares cartographic and demographic data from the U.S. Census Bureau to provide an obvious supplement to Open Environments Block Group publications.These results do not reflect any proprietary or predictive model. Rather, they extract from Census Bureau results with some proportions and aggregation rules applied. For additional support or more detail, please see the Census Bureau citations below. Cartographics refer to shapefiles shared in the Census TIGER/Line publications. Block Group areas are updated annually, with major revisions accompanying the Decennial Census at the turn of each decade. These shapes are useful for visualizing estimates as a map and relating geographies based upon geo-operations like overlapping. This data is kept in a geodatabase file format and requires the geopandas package and its supporting fiona and DAL software. Demographics are taken from popular variables in the American Community Survey (ACS) including age, race, income, education and family structure. This data simply requires csv reader software or pythons pandas package. While the demographic data has many columns, the cartographic data has a very, very large column called "geometry" storing the many-point boundaries of each shape. So, this process saves the data separately, with demographics columns in a csv file and geometry in a gpd file needed an installation of geopandas, fiona and DAL software. More details on the ACS variables selected and derivation rules applied can be found in the commentary docstrings in the source code found here: https://github.com/OpenEnvironments/blockgroupdemographics. ## Files While the demographic data has many columns, the cartographic data has a very, very large column called "geometry" storing the many-point boundaries of each shape. So, this process saves the data separately, with demographics columns in a csv file named YYYYblcokgroupdemographics.csv. The cartographic column, 'geometry', is shared as file named YYYYblockgroupdemographics-geometry.pkl. This file needs an installation of geopandas, fiona and DAL software.

U.S. Census Grids (Summary File 1), 2000: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats for 50 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

About this dataset

Context

The dataset tabulates the Science Hill population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Science Hill. The dataset can be utilized to understand the population distribution of Science Hill by age. For example, using this dataset, we can identify the largest age group in Science Hill.

Key observations

The largest age group in Science Hill, KY was for the group of age Under 5 years years with a population of 84 (10.63%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Science Hill, KY was the 85 years and over years with a population of 0 (0%). 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

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Science Hill is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Science Hill total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Science Hill Population by Age. You can refer the same here

Dataset

This dataset was created by A Luqman Shamsudin

Released under Database: Open Database, Contents: Database Contents

Contents

THE ADVANCED ENVIRONMENTAL SCIENCE AND BIOLOGY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for high school biology education are now freely available.The Advanced Environmental Science and Biology GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading elementary textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device/laptop agnostic. The activities harmonize with the Next Generation Science Standards and AP Environmental Science benchmarks. Activity topics include:Teachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

n = 85.

Context

This dataset is prepared to help with the analysis of covid-19 data.

Content

It contains consolidated data from www.worldlifeexpectancy.com which describes the mortality rate for countries due to lung disease, asthma, influenza and pneumonia.

Acknowledgements

The data wouldn't be here without the help of www.worldlifeexpectancy.com which has consolidated data from WORLD HEALTH ORGANIZATION.

Inspiration

Covid-19 research

The demographic representation of scientists featured in biology curricular materials do not match that of the undergraduate biology student population or of the U.S. population. In this lesson, we promote awareness of inequity in science through an exercise that encourages students to think about who is depicted as scientists in science curricular materials—specifically, biology textbooks. After a brief lecture on the scientific method, students read an excerpt from the introduction of a peer-reviewed publication that provides background information on the importance of representation in science. Next, students collect data from their own biology textbook about the representation of scientists who possess different identities and make a table depicting their results. Then, students fill in predictive graphs about demographic representation over time with respect to scientist identities including perceived gender and race/ethnicity. Students compare their predictions with the results from the peer-reviewed article and discuss the implications of the results. Finally, students apply their new knowledge by designing an experiment that would examine representation of an alternative scientist identity, such as age. Students conclude by answering questions that gauge their knowledge of the scientific method. This activity uses a peer-reviewed publication as well as authentic data generated by the student to increase ideological awareness and teach societal influences on the process of science.

Primary Image: Many stacked textbooks. Creative Commons Attribution-Share Alike 4.0 Downloaded from Wikimedia Commons on May 30, 2023 by authors.