Calculation of Integral Indicators Using Indicative Factors In The Statistical Study of Changes In Demographic Processes
DOI:
https://doi.org/10.31150/ajebm.v7i12.3147Keywords:
Demographic Processes, Statistical Analysis, Integral Indicators, Indicative Factors, Population Dynamics, Birth Rates, Mortality Rates, Migration Patterns, Forecasting, Evidence-Based PoliciesAbstract
The methodology for calculating integral indicators by indicative factors combining statistical analysis of changes in demographic processes is studied in this article. This takes a view of the demographic integration of birth rates, mortality rates, migration patterns for constructing an integral framework of the population dynamics. Statistical tools are shown to be essential in uncovering trends, predicting demographic changes, and developing evidence based policies to help solve the demographic challenges discussed in the study. The paper also provides practical application of these methods to solve the socio-economic challenges related to demographic changes.
Downloads
References
A. B. Kassay, “Statistical-based spatial analysis on urban water management under changing environments: a case study of Hawassa, Ethiopia,” Environ Res Commun, vol. 6, no. 7, 2024, doi: 10.1088/2515-7620/ad59f3.
H. Chweidan, “Statistical Methods and Machine Learning Algorithms for Investigating Metabolic Syndrome in Temporomandibular Disorders: A Nationwide Study,” Bioengineering, vol. 11, no. 2, 2024, doi: 10.3390/bioengineering11020134.
M. M. Ahmmed, “Statistical exploration and projection of SDG-3 in Bangladesh through DHS: A study on data-driven perspectives using logistic regression,” Procedia Comput Sci, vol. 235, pp. 2112–2123, 2024, doi: 10.1016/j.procs.2024.04.200.
M. M. Broekman, “Statistical groupings of mental and social health measurements correlate with musculoskeletal capability – A cross sectional study,” J Psychosom Res, vol. 178, 2024, doi: 10.1016/j.jpsychores.2024.111603.
T. Anılan, “Statistical analysis of flood risk perception: a case study for Eastern Black Sea Basin, Turkey,” Natural Hazards, vol. 120, no. 9, pp. 8743–8760, 2024, doi: 10.1007/s11069-024-06548-7.
B. Chun, “Scenario-based statistical analysis for PM2.5 concentration: A case study of Seoul, South Korea,” Environmental Challenges, vol. 15, 2024, doi: 10.1016/j.envc.2024.100942.
N. J. Anderson, “The changing landscape of head and neck cancer radiotherapy patients: is high-risk, prolonged feeding tube use indicative of on-treatment weight loss?,” J Med Radiat Sci, vol. 66, no. 4, pp. 250–258, 2019, doi: 10.1002/jmrs.349.
H. H. F. Alves, “The acetylcholinesterase as indicative of intoxication for pesticide in farmers of conventional and organic cultivation,” Brazilian Journal of Biology, vol. 81, no. 3, pp. 632–641, 2021, doi: 10.1590/1519-6984.227875.
Y. Sumi, “Minor hallucinations in isolated rapid eye movement sleep behavior disorder indicative of early phenoconversion: A preliminary study,” Acta Neurol Scand, vol. 145, no. 3, pp. 348–359, 2022, doi: 10.1111/ane.13555.
Y. Huang, “Computed tomography-based body composition indicative of diabetes after hypertriglyceridemic acute pancreatitis,” Diabetes Res Clin Pract, vol. 217, 2024, doi: 10.1016/j.diabres.2024.111862.
J. D. Sánchez-Martínez, “Delimitation of rural and urban areas from spatial data in statistical grids: the province of Jaén (Spain) as a case study,” J Maps, vol. 20, no. 1, 2024, doi: 10.1080/17445647.2024.2301980.
D. Ortiz-Reinoso, “Comparative Study of Multivariate Statistical Methods for Predicting the Academic Performance of Students at the University of Guayaquil,” Lecture Notes in Networks and Systems, vol. 870, pp. 81–89, 2024, doi: 10.1007/978-3-031-51982-6_8.
J. D. Ivory, “A scoping review protocol to identify clinical signs, symptoms and biomarkers indicative of biofilm presence in chronic wounds,” HRB Open Res, vol. 4, 2021, doi: 10.12688/hrbopenres.13300.2.
Y. Zhang, “Analysis of Social Media Behavior of Students in Colleges and Universities and Its Indicative Implications for Mental Health,” Applied Mathematics and Nonlinear Sciences, vol. 9, no. 1, 2024, doi: 10.2478/amns-2024-0970.
E. Bellier, “A statistical population reconstruction model for wildlife populations: A case study with white-tailed deer and fisher,” Ecosphere, vol. 15, no. 6, 2024, doi: 10.1002/ecs2.4878.
J. Zhou, “A review of forest size structure studies: from statistical description to theoretical deduction,” Chinese Journal of Plant Ecology, vol. 48, no. 6, pp. 675–689, 2024, doi: 10.17521/cjpe.2023.0301.
United Nations, Department of Economic and Social Affairs, Population Division. (2023). World Population Prospects 2022: Summary of Results. United Nations Publications.
Eurostat. (2023). Population Statistics. Retrieved from https://ec.europa.eu/eurostat.
World Bank. (2022). World Development Indicators: Population Dynamics. Retrieved from https://databank.worldbank.org.
OECD. (2021). Demographic Trends and Their Implications for Development. OECD Publishing. Retrieved from https://www.oecd.org.
