Today, population census results are not only fundamental for population counting but also for providing various information to many organizations and people who make research and take decisions about human-related issues. However, statistics produced on the basis of administrative divisions in Turkey are inadequate to meet the needs of most In this study, a new census geography is aimed for Turkey using Geographic Information Systems and Multi Criteria Decision Making methodologies. This new census geography is for statistical purposes only, independent from legal boundaries and generated by the concept of small area statistics. New rules and methodologies are created by taking the United States and the United Kingdom systems as models to reach to the main aim, and then they are applied on a case study area, &Ccedil / ankaya District in Ankara. Through this application process, firstly all the collected graphical and nongraphical raw data are geo-referenced and combined in a common geodatabase. Secondly, this geodatabase is used to understand the differentiation of quality of life indicators across the case study area. This pattern is then used to draw the boundaries of small statistical units of the new census geography in terms of the previously defined population sizes. In conclusion, a nationwide standard census geography hierarchy, which ranges between national level at the top and block level at the bottom, is proposed for use in 2010 Population Census and afterwards.

Thesis (Ph.D. (Statistics)) -- University of Limpopo, 2019 / This study presents the application of Direct and Indirect methods of Small AreaEstimation(SAE)techniques. Thestudyisaimedatestimatingthetrends and the proportions of households accessing water, sanitation, and electricity for lighting at small areas of the Limpopo Province, South Africa. The study modified Statistics South Africa’s General Household Survey series 2009-2015 and Census 2011 data. The option categories of three variables: Water, Sanitation and Electricity for lighting, were re-coded. Empirical Bayes and Hierarchical Bayes models known as Markov Chain Monte Carlo (MCMC) methods were used to refine estimates in SAS. The Census 2011 data aggregated in ‘Supercross’ was used to validate the results obtained from the models. The SAE methods were applied to account for the census undercoverage counts and rates. It was found that the electricity services were more prioritised than water and sanitation in the Capricorn District of the Limpopo Province. The greatest challenge, however, lies with the poor provision of sanitation services in the country, particularly in the small rural areas. The key point is to suggestpolicyconsiderationstotheSouthAfricangovernmentforfutureequitable provisioning of water, sanitation and electricity services across the country.