This statistic depicts the age distribution in the United States from 2013 to 2023. In 2023, about 17.59 percent of the U.S. population fell into the 0-14 year category, 64.97 percent into the 15-64 age group and 17.43 percent of the population were over 65 years of age. The increasing population of the United States The United States of America is one of the most populated countries in the world, trailing just behind China and India. A total population count of around 320 million inhabitants and a more-or-less steady population growth over the past decade indicate that the country has steadily improved its living conditions and standards for the population. Leading healthier lifestyles and improved living conditions have resulted in a steady increase of the life expectancy at birth in the United States. Life expectancies of men and women at birth in the United States were at a record high in 2012. Furthermore, a constant fertility rate in recent years and a decrease in the death rate and infant mortality, all due to the improved standard of living and health care conditions, have helped not only the American population to increase but as a result, the share of the population younger than 15 and older than 65 years has also increased in recent years, as can be seen above.

This dataset contains the entire concept structure of UMLS Metathesaurus for the semantic type "Age Group". One of the primary purposes of this dataset is to connect different names for all the concepts for a specific Semantic Type. There are 125 semantic types in the Semantic Network. Every Metathesaurus concept is assigned at least one semantic type; very few terms are assigned as many as five semantic types.

Image Classification Age Range Labels

This repository uses the following labels to categorize age ranges in image classification tasks:

[!Warning] labels_list = ['0-12', '13-20', '21-44', '45-64', '65+']

the values are age range in iamge classification give the README.MD for Repository

0-12: Images depicting individuals aged 0 to 12 years old. 13-20: Images depicting individuals aged 13 to 20 years old. 21-44: Images depicting individuals aged 21 to 44 years old. 45-64: Images… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Age-Classification-Set.

Feature set developed to support "Predicting Age Groups of Twitter Users Based on Language and Metadata Features" by Morgan-Lopez et al. (2017). The feature set encompasses candidate variables for each of the four models referenced in the paper ("Tweet Language Only","Twitter Handle Metadata Only","Tweet Language Use and Handle Metadata", and "WWBP Words"). Description of target variables listed below -- for further description of features and methodology please reference manuscript.Target Variablesage_cat: User age category {"1" : 13-17, "2" : 18-24, "3" : 25-50} age_cat_sen: User age category used for sensitivity analysis {"1" : 13-17, "2" : 18-29, "3" : 30-50}user_age: User ageOtherrand_id: Random ID assigned to Twitter user

During the second quarter of 2022, ****** apps hosted and distributed in the Google Play Store registered higher engagement among global users aged between 18 and 24 years. ******* users were the most active demographic across all examined app categories, with approximately **** of all downloads in the music and audio category generated in the Google Play Store coming from users in the 18 to 24 demographic group. Approximately ***** in ** users downloading news and magazines apps were aged between 50 and 64 years, while ***percent of parenting apps were downloaded by users aged 25 and 34 years.

This layer shows age and sex demographics. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to the percent of the population ages 18 to 24 years old. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the filter settings. Layer includes:Key demographicsTotal populationMale total populationFemale total populationPercent male total population (calculated)Percent female total population (calculated)Age and other indicatorsTotal population by AGE (various ranges)Total population by SELECTED AGE CATEGORIES (various ranges)Total population by SUMMARY INDICATORS (including median age, sex ratio, age dependency ratio, old age dependency ratio, child dependency ratio)Percent total population by AGE (various ranges)Percent total population by SELECTED AGE CATEGORIES (various ranges)Male by ageMale total population by AGE (various ranges)Male total population by SELECTED AGE CATEGORIES (various ranges)Male total population Median age (years)Percent male total population by AGE (various ranges)Percent male total population by SELECTED AGE CATEGORIES (various ranges)Female by ageFemale total population by AGE (various ranges)Female total population by SELECTED AGE CATEGORIES (various ranges)Female total population Median age (years)Percent female total population by AGE (various ranges)Percent female total population by SELECTED AGE CATEGORIES (various ranges)A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Current Vintage: 2018-2022ACS Table(s): S0101 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community SurveyDate of Census update: Dec 15, 2023Data Preparation: Data table downloaded and joined with Census Tract boundaries that are within or adjacent to the City of Tempe boundaryNational Figures: data.census.gov

Estimate Population By Category Of Patients & Age Groups By State Malaysia, 2016

This dataset provides information about different age categories along with population and percentage in the town of Dumfries in the year 2020

Age Classification

## Overview

Age Classification is a dataset for classification tasks - it contains Person Age Q8s1 annotations for 9,910 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

As of February 2024, over a third of online users worldwide were aged between 25 and 34 years. Website visitors in this age bracket constituted the biggest group of online users worldwide. Also, 19 percent of global online users were aged 18 to 24 years. The global digital population aged 65 or older represented approximately 4.2 percent of all internet users worldwide. Social media usage and Meta Social media is a major driver of internet use, with a global penetration rate of 62.2 percent. On average, internet users spend 143 minutes per day on social media, highlighting its significant impact on daily online activities. The usage of social media is mostly dominated by Meta platforms, which own four of the largest social media platforms. Facebook leads the ranking with over three billion active users, followed by Instagram and WhatsApp. Instagram's global popularity Meta’s social video platform, Instagram, had long been one of the most engaging social media platforms worldwide, and it was projected to reach 1.44 billion monthly active users. Instagram was particularly favored by users aged 18 to 34, thanks to its ability to offer a variety of interactive content, from images and carousels. This diverse range of content types was a key factor in its popularity among its young user base.

Percentage of individuals who shopped online and percentage of online shoppers by type of good and service purchased over the Internet during the past 12 months.

Vintage 2024 Population projections by race, sex and age group for North Carolina counties. Includes population by race (American Indian/Alaska Native), Asian & Pacific Islander (Asian), Black, White, Other (includes persons identified as two or more races). In some counties not all race groups will be reported separately. For population of less than 250 for any race group, the population by age will be reported within the other category and the "group n" for the other category show a number larger than 1 indicating that the other category includes population from other race groups that are separately reported for other counties. For this reason, users should take care in aggregating race group population across counties.

Living arrangement by age group for the Department of Development Services (DDS) population. Information is reported by the Regional Centers to the DDS and is extracted from the Client Master File (CMF). The Client Master File (CMF) is the primary source of demographic information on individuals receiving services funded by DDS.

This dataset provides information on the number of vehicles in circulation according to vehicle types and age ranges for each of the Canary Islands and municipalities. Annual data since 2010.

This dataset shows the number of new cases of Persons With Disabilities registered by category of disabilities and age group, Malaysia, 2018

This table provides annual data on the estimated population aged 16 and over in the Canary Islands by activity and age groups.

France Job Seekers: Category A: Age: Under 25 data was reported at 506.000 Person th in Oct 2018. This records an increase from the previous number of 490.900 Person th for Sep 2018. France Job Seekers: Category A: Age: Under 25 data is updated monthly, averaging 477.950 Person th from Jan 1996 (Median) to Oct 2018, with 274 observations. The data reached an all-time high of 708.000 Person th in Oct 1996 and a record low of 307.400 Person th in Jun 2001. France Job Seekers: Category A: Age: Under 25 data remains active status in CEIC and is reported by Ministry of Labour, Employment and Health. The data is categorized under Global Database’s France – Table FR.G044: Labour Statistics: Job Seekers.

Statistics on the Employment of Persons with Disabilities: Employed by type of working day and age group. National.

Economically Active Population Survey: Employment rate of people between 20 and 64 years old by age group and Autonomous Community. Annual. Autonomous Communities and Cities.

Participation rate in selected activities over 24 hours, in 5-minute increments, by type of day, gender and age group, 15 years and over, Canada.