41 datasets found
  1. Population of Ireland by age group 2025

    • statista.com
    Updated Apr 25, 2014
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2014). Population of Ireland by age group 2025 [Dataset]. https://www.statista.com/statistics/710767/irish-population-by-age/
    Explore at:
    Dataset updated
    Apr 25, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ireland, Ireland
    Description

    In 2025, there were 435,500 people aged between 40 and 44 in the Republic of Ireland, the most common age group among those provided in this year.

  2. Total population of Ireland 1980-2030

    • statista.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista, Total population of Ireland 1980-2030 [Dataset]. https://www.statista.com/statistics/376906/total-population-of-ireland/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ireland, Ireland
    Description

    The total population of Ireland was 5.42 million people in 2024. Between 1980 and 2024, the total population rose by 1.99 million people, though the increase followed an uneven trajectory rather than a consistent upward trend. The total population will steadily rise by 290,000 people over the period from 2024 to 2030, reflecting a clear upward trend.This indicator describes the total population in the country at hand. This total population of the country consists of all persons falling within the scope of the census.

  3. M

    Roi Et, Thailand Metro Area Population | Historical Data | Chart | 1950-2025...

    • macrotrends.net
    csv
    Updated Oct 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    MACROTRENDS (2025). Roi Et, Thailand Metro Area Population | Historical Data | Chart | 1950-2025 [Dataset]. https://www.macrotrends.net/datasets/global-metrics/cities/205961/roi-et/population
    Explore at:
    csvAvailable download formats
    Dataset updated
    Oct 31, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1950 - Nov 21, 2025
    Area covered
    Thailand
    Description

    Historical dataset of population level and growth rate for the Roi Et, Thailand metro area from 1950 to 2025.

  4. Population of Ireland 1951-2025

    • statista.com
    Updated Sep 3, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Population of Ireland 1951-2025 [Dataset]. https://www.statista.com/statistics/537430/ireland-total-population/
    Explore at:
    Dataset updated
    Sep 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ireland, Ireland
    Description

    In 2025, the population of the Republic of Ireland was approximately **** million, compared with **** million in 2024.

  5. G

    Population Health ROI Assessment Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Aug 29, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Growth Market Reports (2025). Population Health ROI Assessment Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/population-health-roi-assessment-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Aug 29, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Population Health ROI Assessment Market Outlook



    According to our latest research, the global Population Health ROI Assessment market size in 2024 stands at USD 2.13 billion, reflecting the increasing adoption of advanced analytics and health management solutions across the healthcare sector. The market is expected to demonstrate robust growth, with a projected CAGR of 15.7% from 2025 to 2033. By the end of 2033, the market size is forecasted to reach approximately USD 6.65 billion. This significant expansion is attributed to the growing emphasis on value-based care, rising healthcare costs, and the need for measurable returns on investment in population health initiatives. As healthcare systems globally pivot toward data-driven strategies, the demand for comprehensive ROI assessment tools is poised to surge, ensuring sustained market momentum over the next decade.




    One of the primary growth drivers for the Population Health ROI Assessment market is the accelerating shift towards value-based healthcare models. Healthcare providers and payers are under increasing pressure to demonstrate the financial and clinical impact of population health management programs. By leveraging robust ROI assessment frameworks, organizations can quantify the benefits of preventive care, chronic disease management, and coordinated care interventions. This shift is further supported by regulatory mandates and policy incentives that prioritize outcomes over volume, compelling stakeholders to adopt technologies that can accurately measure and optimize health investments. The integration of advanced analytics, artificial intelligence, and real-time data processing is enabling more precise and actionable ROI insights, thereby fueling market growth.




    Another significant growth factor is the proliferation of digital health technologies and the expansion of healthcare data ecosystems. The widespread adoption of electronic health records (EHRs), wearable devices, and remote monitoring solutions has generated vast amounts of patient data. Population health ROI assessment platforms are increasingly leveraging this data to deliver comprehensive analyses that support strategic decision-making. These platforms enable healthcare organizations to identify high-risk populations, allocate resources efficiently, and evaluate the effectiveness of interventions at both individual and community levels. As interoperability standards improve and data integration becomes more seamless, the accuracy and utility of ROI assessments are expected to reach new heights, further boosting market expansion.




    Additionally, the rising focus on cost containment and operational efficiency across the healthcare continuum is propelling the demand for population health ROI assessment solutions. Payers, employers, and government organizations are seeking ways to optimize healthcare spending while improving patient outcomes. By deploying ROI assessment tools, these stakeholders can justify investments in wellness programs, preventive care, and population health initiatives. The ability to demonstrate tangible returns on health interventions is becoming a critical factor in securing funding and sustaining long-term programs. This trend is particularly pronounced in regions with aging populations and increasing prevalence of chronic diseases, where the economic impact of healthcare expenditures is a major concern.



    Healthcare Provider Population Health Management Platforms are becoming increasingly vital in the landscape of population health ROI assessment. These platforms enable healthcare providers to streamline data collection and analysis, facilitating a more comprehensive understanding of patient populations. By integrating various data sources, such as electronic health records and patient management systems, these platforms offer healthcare providers the tools needed to implement effective population health strategies. The ability to track and measure health outcomes across diverse patient groups allows providers to tailor interventions and improve overall care quality. As the demand for value-based care continues to rise, these platforms are essential for demonstrating the tangible benefits of population health initiatives, thereby justifying investments and fostering sustainable healthcare practices.



    <p&

  6. Population of the Republic of Ireland 1821-2011

    • statista.com
    Updated Jul 10, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2019). Population of the Republic of Ireland 1821-2011 [Dataset]. https://www.statista.com/statistics/1015403/total-population-republic-ireland-1821-2011/
    Explore at:
    Dataset updated
    Jul 10, 2019
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ireland, Ireland
    Description

    The island of Ireland is split into 32 different counties, and from 1800 until 1921 the whole island was a part of the United Kingdome of Great Britain and Ireland (although Britain had been a controlling presence on the island for considerably longer than this). In 1921 the island was split into two separate states, where the six counties with the highest population of Protestants formed part of the United Kingdom of Great Britain and Northern Ireland, and the other 26 counties became the Independent Republic of Ireland. From 1821 until 1841, the population of these 26 counties was growing steadily, until the Great Famine from 1845 to 1849 swept across the island, particularly devastating the west and south.

    The famine was caused by a Europe-wide potato blight that contributed to mass starvation and death throughout the continent, although it's impact on Ireland was much harsher than anywhere else. The potato blight affected Ireland so severely as the majority of potatoes in Ireland were of a single variety which allowed the disease to spread much faster than in other countries. People in the west and south of Ireland were particularly dependent on potatoes, and these areas were affected more heavily than the north and west, where flax and cereals were the staple. As the potato blight spread, the population became increasingly reliant on dairy and grain products, however a lot of these resources were relocated by the British military to combat food shortages in Britain. Due to disproportional dependency on potatoes, and mismanagement by the British government, over one million people died and a further one million emigrated. The Great Famine lasted from just 1845 to 1849, but it's legacy caused almost a century of population decline, and to this day, the population of Ireland has never exceeded it's pre-famine levels.

    The population decline continued well into the twentieth century, during which time the Republic of Ireland achieved independence from the British Empire. After centuries of fighting and rebellion against British rule, Irish nationalists finally gained some independence from Britain in 1921, establishing an Irish Republic in the 26 counties. There was a lot of conflict in Ireland in the early 1900s, through the War of Independence and Irish Civil War, however the population of the Republic began growing again from the 1960s onwards as the quality of life improved and the emigration rate declined. The population was at it's lowest from 1926 to 1971, where it remained at just under three million, but in the following fifty years the population has grown by over two million people.

  7. The demographics and characteristics of the selected population.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    • +1more
    xls
    Updated Jun 4, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Muwei Li; Kenichi Oishi; Xiaohai He; Yuanyuan Qin; Fei Gao; Susumu Mori (2023). The demographics and characteristics of the selected population. [Dataset]. http://doi.org/10.1371/journal.pone.0105563.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Muwei Li; Kenichi Oishi; Xiaohai He; Yuanyuan Qin; Fei Gao; Susumu Mori
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The between-group differences in age and MMSE were assessed with the student's t-test. The differences in gender were evaluated by a two-sided Pearson Chi-Square test.

  8. Demographic information of the studied population.

    • plos.figshare.com
    xls
    Updated Jun 16, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Xiaojing Long; Lifang Chen; Chunxiang Jiang; Lijuan Zhang (2023). Demographic information of the studied population. [Dataset]. http://doi.org/10.1371/journal.pone.0173372.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Xiaojing Long; Lifang Chen; Chunxiang Jiang; Lijuan Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Demographic information of the studied population.

  9. T

    Thailand GDP: Roi Et: Population (1,000 Persons)

    • ceicdata.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com, Thailand GDP: Roi Et: Population (1,000 Persons) [Dataset]. https://www.ceicdata.com/en/thailand/regional-gdp-sna93-northeastern-current-price-rev-4/gdp-roi-et-population-1000-persons
    Explore at:
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Thailand
    Description

    Thailand GDP: Roi Et: Population (1,000 Persons) data was reported at 1,071.749 Person th in 2016. This records a decrease from the previous number of 1,074.449 Person th for 2015. Thailand GDP: Roi Et: Population (1,000 Persons) data is updated yearly, averaging 1,176.594 Person th from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 1,284.074 Person th in 2000 and a record low of 1,071.749 Person th in 2016. Thailand GDP: Roi Et: Population (1,000 Persons) data remains active status in CEIC and is reported by National Economic and Social Development Board. The data is categorized under Global Database’s Thailand – Table TH.A076: Regional GDP: SNA93: Northeastern: Current Price (Rev. 4).

  10. f

    Demographics of the KORA study population.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 1, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Sophia D. Heber; Holger Hetterich; Roberto Lorbeer; Christian Bayerl; Jürgen Machann; Sigrid Auweter; Corinna Storz; Christopher L. Schlett; Konstantin Nikolaou; Maximilian Reiser; Annette Peters; Fabian Bamberg (2023). Demographics of the KORA study population. [Dataset]. http://doi.org/10.1371/journal.pone.0177154.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Sophia D. Heber; Holger Hetterich; Roberto Lorbeer; Christian Bayerl; Jürgen Machann; Sigrid Auweter; Corinna Storz; Christopher L. Schlett; Konstantin Nikolaou; Maximilian Reiser; Annette Peters; Fabian Bamberg
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data are given as number (percentage) or median (25th and 75th percentile).

  11. Demographic characteristics of the final samples for each task.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Paola Fuentes-Claramonte; Marta Martín-Subero; Pilar Salgado-Pineda; Silvia Alonso-Lana; Ana Moreno-Alcázar; Isabel Argila-Plaza; Aniol Santo-Angles; Anton Albajes-Eizagirre; Maria Anguera-Camós; Antoni Capdevila; Salvador Sarró; Peter J. McKenna; Edith Pomarol-Clotet; Raymond Salvador (2023). Demographic characteristics of the final samples for each task. [Dataset]. http://doi.org/10.1371/journal.pone.0209376.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Paola Fuentes-Claramonte; Marta Martín-Subero; Pilar Salgado-Pineda; Silvia Alonso-Lana; Ana Moreno-Alcázar; Isabel Argila-Plaza; Aniol Santo-Angles; Anton Albajes-Eizagirre; Maria Anguera-Camós; Antoni Capdevila; Salvador Sarró; Peter J. McKenna; Edith Pomarol-Clotet; Raymond Salvador
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Demographic characteristics of the final samples for each task.

  12. Radio Broadcasting in Ireland - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Jul 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    IBISWorld (2025). Radio Broadcasting in Ireland - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/ireland/market-research-reports/radio-broadcasting-industry/
    Explore at:
    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2015 - 2030
    Area covered
    Ireland
    Description

    Listener figures for Irish radio have remained strong in recent years, with 90% of adults in Ireland listening to radio stations every week, according to Joint National Listenership Research in 2024. However, the industry's potential listeners now have a variety of alternatives to radio, including streaming services and personal digital audio, which has drawn younger listeners away and left broadcaster’s dependent on the 55-and-over age bracket. Improving internet access and technological developments have led to rapid growth in external competition, although radio access has also expanded, with a 33% hike in digital radio listening and the use of smart speakers and devices for listening. The loss in listening time in set to cause revenue to drop at a compound annual rate of 3.7% over the five years through 2025 to €265.8 million. New listening options have redirected advertising revenue away from traditional radio broadcasters. Marketing departments are shifting focus to digital strategies which wield better return on investment for advertisers. This has caused advertising spot prices for radio stations to fall, contributing to the downward direction of revenue. Revenue is projected to drop 1.8% in 2025 as this trend continues. Ireland’s regional stations, which hold a dominant market share, are best placed to bring back advertising revenue. They can offer more targeted advertising in small markets, contributing to their stronger performance relative to nationwide broadcasts. Revenue is forecast to sink at a compound annual rate of 1.7% to €244 million over the five years through 2030. The trend of younger listeners being drawn away by alternative audio will continue, though the ageing population should support radio listening figures. Managing the transition to new technologies and making the most of the opportunities provided by the internet will be crucial for commercial radio operators.

  13. Data from: A new theoretical performance landscape for suction feeding...

    • zenodo.org
    • data.niaid.nih.gov
    • +1more
    bin, csv
    Updated Jun 10, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Roi Holzman; Roi Holzman (2022). A new theoretical performance landscape for suction feeding reveals adaptive kinematics in a natural population of reef damselfish [Dataset]. http://doi.org/10.5061/dryad.59zw3r2b5
    Explore at:
    csv, binAvailable download formats
    Dataset updated
    Jun 10, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Roi Holzman; Roi Holzman
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Understanding how organismal traits determine performance and, ultimately, fitness is a fundamental goal of evolutionary ecomorphology. However, multiple traits can interact in non-linear and context-dependent ways to affect performance, hindering efforts to place natural populations with respect to performance peaks or valleys. Here, we used an established mechanistic model of suction-feeding performance (SIFF) derived from hydrodynamic principles to estimate a theoretical performance landscape for zooplankton prey capture. This performance space can be used to predict prey capture performance for any combination of six morphological and kinematic trait values. We then mapped in situ high-speed video observations of suction feeding in a natural population of a coral reef zooplanktivore, Chromis viridis, onto the performance space to estimate the population's location with respect to the topography of the performance landscape. Although the kinematics of the natural population closely matched regions of high performance in the landscape, the population was not located on a performance peak. Individuals were furthest from performance peaks on the peak gape, ram speed and mouth opening speed trait axes. Moreover, we found that the trait combinations in the observed population were associated with higher performance than expected by chance, suggesting that these combinations are under selection. Our results provide a framework for assessing whether natural populations occupy performance optima.

  14. Mortality, ethnicity, and country of birth on a national scale, 2001–2013: A...

    • plos.figshare.com
    docx
    Updated Jun 5, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Raj S. Bhopal; Laurence Gruer; Genevieve Cezard; Anne Douglas; Markus F. C. Steiner; Andrew Millard; Duncan Buchanan; S. Vittal Katikireddi; Aziz Sheikh (2023). Mortality, ethnicity, and country of birth on a national scale, 2001–2013: A retrospective cohort (Scottish Health and Ethnicity Linkage Study) [Dataset]. http://doi.org/10.1371/journal.pmed.1002515
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Raj S. Bhopal; Laurence Gruer; Genevieve Cezard; Anne Douglas; Markus F. C. Steiner; Andrew Millard; Duncan Buchanan; S. Vittal Katikireddi; Aziz Sheikh
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Scotland
    Description

    BackgroundMigrant and ethnic minority groups are often assumed to have poor health relative to the majority population. Few countries have the capacity to study a key indicator, mortality, by ethnicity and country of birth. We hypothesized at least 10% differences in mortality by ethnic group in Scotland that would not be wholly attenuated by adjustment for socio-economic factors or country of birth.Methods and findingsWe linked the Scottish 2001 Census to mortality data (2001–2013) in 4.62 million people (91% of estimated population), calculating age-adjusted mortality rate ratios (RRs; multiplied by 100 as percentages) with 95% confidence intervals (CIs) for 13 ethnic groups, with the White Scottish group as reference (ethnic group classification follows the Scottish 2001 Census). The Scottish Index of Multiple Deprivation, education status, and household tenure were socio-economic status (SES) confounding variables and born in the UK or Republic of Ireland (UK/RoI) an interacting and confounding variable. Smoking and diabetes data were from a primary care sub-sample (about 53,000 people). Males and females in most minority groups had lower age-adjusted mortality RRs than the White Scottish group. The 95% CIs provided good evidence that the RR was more than 10% lower in the following ethnic groups: Other White British (72.3 [95% CI 64.2, 81.3] in males and 75.2 [68.0, 83.2] in females); Other White (80.8 [72.8, 89.8] in males and 76.2 [68.6, 84.7] in females); Indian (62.6 [51.6, 76.0] in males and 60.7 [50.4, 73.1] in females); Pakistani (66.1 [57.4, 76.2] in males and 73.8 [63.7, 85.5] in females); Bangladeshi males (50.7 [32.5, 79.1]); Caribbean females (57.5 [38.5, 85.9]); and Chinese (52.2 [43.7, 62.5] in males and 65.8 [55.3, 78.2] in females). The differences were diminished but not eliminated after adjusting for UK/RoI birth and SES variables. A mortality advantage was evident in all 12 minority groups for those born abroad, but in only 6/12 male groups and 5/12 female groups of those born in the UK/RoI. In the primary care sub-sample, after adjustment for age, UK/RoI born, SES, smoking, and diabetes, the RR was not lower in Indian males (114.7 [95% CI 78.3, 167.9]) and Pakistani females (103.9 [73.9, 145.9]) than in White Scottish males and females, respectively. The main limitations were the inability to include deaths abroad and the small number of deaths in some ethnic minority groups, especially for people born in the UK/RoI.ConclusionsThere was relatively low mortality for many ethnic minority groups compared to the White Scottish majority. The mortality advantage was less clear in UK/RoI-born minority group offspring than in immigrants. These differences need explaining, and health-related behaviours seem important. Similar analyses are required internationally to fulfil agreed goals for monitoring, understanding, and improving health in ethnically diverse societies and to apply to health policy, especially on health inequalities and inequities.

  15. v

    Catégories Sociales Bois-le-Roi

    • ville-data.com
    Updated Sep 28, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ville-data (2025). Catégories Sociales Bois-le-Roi [Dataset]. https://ville-data.com/categories-sociales/Bois-le-Roi-27-27073
    Explore at:
    Dataset updated
    Sep 28, 2025
    Dataset authored and provided by
    Ville-data
    License

    https://www.etalab.gouv.fr/licence-ouverte-open-licence/https://www.etalab.gouv.fr/licence-ouverte-open-licence/

    Area covered
    Bois-le-Roi
    Description

    répartition par catégories socioprofessionnelles de la population de Bois-le-Roi

  16. n

    Data from: Multiple sexual signals and behavioral reproductive isolation in...

    • data.niaid.nih.gov
    • data-staging.niaid.nih.gov
    • +1more
    zip
    Updated May 8, 2013
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yoni Vortman; Arnon Lotem; Roi Dor; Irby Lovette; Rebecca J. Safran (2013). Multiple sexual signals and behavioral reproductive isolation in a diverging population [Dataset]. http://doi.org/10.5061/dryad.g8n63
    Explore at:
    zipAvailable download formats
    Dataset updated
    May 8, 2013
    Authors
    Yoni Vortman; Arnon Lotem; Roi Dor; Irby Lovette; Rebecca J. Safran
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Israel, Middle-East
    Description

    Sexual trait divergence has been shown to play a role in the evolution of reproductive isolation. While variation in multiple sexual signals is common among closely related species, little is known about the role of these different axes of phenotype variation with respect to the evolution of behavioral reproductive isolation. Here we study a unique population of barn swallows (Hirundo rustica transitiva) which can only be distinguished phenotypically from its neighboring populations based on two features of male plumage: exaggerated expression of both long tail streamers and dark ventral coloration. Using phenotype manipulation experiments, we conducted a paternity study to examine whether both traits are sexually selected. Our results show that an exaggerated form of the local male phenotype (with both tail elongation and color darkening) is favored by local females whereas males whose phenotypes were manipulated to look like males of neighboring subspecies suffered paternity losses from their social mates. These results confirm the multiple signaling role of the unique tail and color combination in our diverging population and suggest a novel possibility according to which multiple sexual signals may also be used to discriminate among males from nearby populations when pre-zygotic reproductive isolation is adaptive.

  17. Consumer Marketing Data API | Tailored Consumer Insights | Target with...

    • datarade.ai
    Updated Oct 27, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Success.ai (2021). Consumer Marketing Data API | Tailored Consumer Insights | Target with Precision | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/consumer-marketing-data-api-tailored-consumer-insights-ta-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    United Arab Emirates, Senegal, Hong Kong, Vanuatu, Estonia, Sweden, Madagascar, Turkey, Philippines, Burundi
    Description

    Success.ai’s Consumer Marketing Data API empowers your marketing, analytics, and product teams with on-demand access to a vast and continuously updated dataset of consumer insights. Covering detailed demographics, behavioral patterns, and purchasing histories, this API enables you to go beyond generic outreach and craft tailored campaigns that truly resonate with your target audiences.

    With AI-validated accuracy and support for precise filtering, the Consumer Marketing Data API ensures you’re always equipped with the most relevant data. Backed by our Best Price Guarantee, this solution is essential for refining your strategies, improving conversion rates, and driving sustainable growth in today’s competitive consumer landscape.

    Why Choose Success.ai’s Consumer Marketing Data API?

    1. Tailored Consumer Insights for Precision Targeting

      • Access verified demographic, behavioral, and purchasing data to understand what consumers truly value.
      • AI-driven validation ensures 99% accuracy, minimizing wasted spend and improving engagement outcomes.
    2. Comprehensive Global Reach

      • Includes consumer profiles from diverse regions and markets, enabling you to scale campaigns and discover emerging opportunities.
      • Adapt swiftly to new markets, product launches, and shifting consumer preferences with real-time data at your fingertips.
    3. Continuously Updated and Real-Time Data

      • Receive ongoing updates that reflect evolving consumer behaviors, interests, and market trends.
      • Respond quickly to seasonal changes, competitor moves, and industry disruptions, ensuring your campaigns remain timely and relevant.
    4. Ethical and Compliant

      • Fully adheres to GDPR, CCPA, and other global data privacy regulations, guaranteeing responsible and lawful data usage.

    Data Highlights:

    • Detailed Demographics: Age, gender, location, and income levels to refine targeting and messaging.
    • Behavioral Insights: Interests, browsing patterns, and content consumption habits to anticipate consumer needs.
    • Purchasing History: Understand consumer spending, brand loyalty, and product preferences to tailor promotions effectively.
    • Real-Time Updates: Keep pace with evolving consumer tastes, ensuring your strategies remain forward-focused and competitive.

    Key Features of the Consumer Marketing Data API:

    1. Granular Targeting and Segmentation

      • Query the API to segment consumers by demographics, interests, past purchases, or engagement patterns.
      • Focus campaigns on the most receptive audiences, enhancing conversion rates and ROI.
    2. Flexible and Seamless Integration

      • Easily integrate the API into CRM systems, marketing automation tools, or analytics platforms.
      • Streamline workflows and eliminate manual data imports, freeing resources for strategic initiatives.
    3. Continuous Data Enrichment

      • Refresh consumer profiles with the latest data, ensuring every decision is backed by current insights.
      • Reduce data decay and maintain top-notch data hygiene to maximize long-term marketing effectiveness.
    4. AI-Driven Validation

      • Rely on advanced AI validation techniques to guarantee high-quality data accuracy and reliability.
      • Increase confidence in your campaigns and decrease budget wasted on irrelevant targets.

    Strategic Use Cases:

    1. Highly Personalized Marketing Campaigns

      • Deliver tailored offers, recommendations, and content that align with individual consumer preferences.
      • Boost engagement and loyalty by making every touchpoint relevant and meaningful.
    2. Market Expansion and Product Launches

      • Identify segments most receptive to new products or services, ensuring successful market entry.
      • Stay ahead of consumer demands, evolving your product line and marketing mix to meet changing preferences.
    3. Competitive Analysis and Trend Forecasting

      • Leverage consumer insights to anticipate emerging trends and outpace competitors in capturing new markets.
      • Adjust marketing strategies proactively to capitalize on seasonal, cultural, or economic shifts.
    4. Customer Retention and Loyalty Programs

      • Use historical purchase and engagement data to identify at-risk customers and implement retention strategies.
      • Cultivate brand advocates by delivering personalized offers and exclusive perks to loyal consumers.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality consumer marketing data at unmatched prices, ensuring maximum ROI for your outreach efforts.
    2. Seamless Integration

      • Easily incorporate the API into existing workflows, eliminating data silos and manual data management.
    3. Data Accuracy with AI Validation

      • Depend on 99% accuracy to guide data-driven decisions, refine targeting, and elevate your marketing initiatives.
    4. Customizable and Scalable Solutions

      • Tailor datasets to focus on specific demog...
  18. SDG-Accessibility in percentage and total amount of individuals with access...

    • plos.figshare.com
    xls
    Updated Apr 21, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dorothee Stiller; Michael Wurm; Marta Sapena; Simon Nieland; Stefan Dech; Hannes Taubenböck (2025). SDG-Accessibility in percentage and total amount of individuals with access to public transport according to each transport type in ROI 1 for (a) formal and (b) semiformal transport. The analysis is conducted using population data from three distinct datasets: 1) cadaster, 2) remote sensing: fine-scaled regional approach, and 3) remote sensing: global approach. [Dataset]. http://doi.org/10.1371/journal.pone.0321691.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 21, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Dorothee Stiller; Michael Wurm; Marta Sapena; Simon Nieland; Stefan Dech; Hannes Taubenböck
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    SDG-Accessibility in percentage and total amount of individuals with access to public transport according to each transport type in ROI 1 for (a) formal and (b) semiformal transport. The analysis is conducted using population data from three distinct datasets: 1) cadaster, 2) remote sensing: fine-scaled regional approach, and 3) remote sensing: global approach.

  19. v

    Catégories Sociales Marly-le-Roi

    • ville-data.com
    Updated Sep 28, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ville-data (2025). Catégories Sociales Marly-le-Roi [Dataset]. https://ville-data.com/categories-sociales/Marly-le-Roi-78-78372
    Explore at:
    Dataset updated
    Sep 28, 2025
    Dataset authored and provided by
    Ville-data
    License

    https://www.etalab.gouv.fr/licence-ouverte-open-licence/https://www.etalab.gouv.fr/licence-ouverte-open-licence/

    Area covered
    Marly-le-Roi
    Description

    répartition par catégories socioprofessionnelles de la population de Marly-le-Roi

  20. v

    Catégories Sociales Choisy-le-Roi

    • ville-data.com
    Updated Sep 28, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ville-data (2025). Catégories Sociales Choisy-le-Roi [Dataset]. https://ville-data.com/categories-sociales/Choisy-le-Roi-94-94022
    Explore at:
    Dataset updated
    Sep 28, 2025
    Dataset authored and provided by
    Ville-data
    License

    https://www.etalab.gouv.fr/licence-ouverte-open-licence/https://www.etalab.gouv.fr/licence-ouverte-open-licence/

    Area covered
    Choisy-le-Roi
    Description

    répartition par catégories socioprofessionnelles de la population de Choisy-le-Roi

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2014). Population of Ireland by age group 2025 [Dataset]. https://www.statista.com/statistics/710767/irish-population-by-age/
Organization logo

Population of Ireland by age group 2025

Explore at:
8 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 25, 2014
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Ireland, Ireland
Description

In 2025, there were 435,500 people aged between 40 and 44 in the Republic of Ireland, the most common age group among those provided in this year.

Search
Clear search
Close search
Google apps
Main menu