Prof. Eric Mwambene

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https://hdl.handle.net/10566/1678

Prof. Eric Mwambene

Position: Associate Professor
Department: Department of Mathematics
Faculty: Faculty of Natural Sciences
Qualifications: DSc (Vienna), MSc (UZ), MSc (London), BSc (Hons)(Unima)
My publications in this repository
More about me: here and here
Tel: 021 959 3021
Fax: 021 959 1241
Email: emwambene@uwc.ac.za

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Browsing by Author "Regassa, Nigatu"

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    An assessment of the age reporting in Tanzania population census
    (Academic Research Publishing, 2012) Mwambene, Eric; Appunni, Sathiya Susuman; Hamisi, Hamisi F.; Lougue, Siaka; Regassa, Nigatu; Ogujiuba, Kanayo
    The objective of this paper is to provide data users with a worldwide assessment of the age reporting in the Tanzania Population Census 2012 data. Many demographic and socio-economic data are age-sex attributed. However, a variety of irregularities and misstatements are noted with respect to age-related data and sex ratio data because of its biological differences between the genders. Noting the misstatement / misreporting, inconsistence of age data regardless of its significant importance in demographic and epidemiological studies, this study assess the quality of the 2012 Tanzania Population and Housing Census data relative to age. Data were downloaded from Tanzania National Bureau of Statistics. Age heaping and digit preference were measured using summary indices viz., Whipple‟s index, Myers‟ blended index, and Age-Sex Accuracy index. The recorded Whipple‟s index for both sexes was 154.43, where males had the lower index of about 152.65 while females had the higher index of about 156.07. For Myers‟ blended index, the prefrences were at digits „0‟ and „5‟ while avoidance were at digits „1‟ and „3‟ for both sexes. Finally, the age-sex index stood at 59.8 where the sex ratio score was 5.82, and the age ratio scores were 20.89 and 21.4 for males and female respectively. The evaluation of the 2012 Population Housing Censes data using the demographic techniques has qualified the data as of poor quality as a result of systematic heaping and digit preferences/avoidances in recorded age. Thus, innovative methods in data collection along with measuring and minimizing errors using statistical techniques should be used to ensure accuracy of age data.