[01] Jadab Kumar Pal, Indian Statistical Institute, Kolkata, India. [02] Barun Kumar Mukhopadhyay, Retired, Population Studies Unit, Indian Statistical Institute, Kolkata, India. [03] H. R. Tewari, Department of Humanities and Social Sciences, IIT Kharagpur, West Bengal, India.

The present paper investigates the quality of age data and the effects of education on it in a small village, Ramna Etbar Nagar in the district of Murshidabad, West Bengal, India. To find out the quality of age data, we critically analyzed single year data on age from the figures particularly ending in preferred digits and disliking of ages ending in odd digits, but age selective migration is assumed to be ineffective in this context. The corresponding graph is drawn in order to see the huge peaks and troughs at the preferred and disliking digits. The study reveals from the values and graph that the quality is not at par with the quality to be deemed necessary for any kind of work related to research and planning. Further, Myers’ index (1940) gives a value (71) which is conducive to the quality is unexpected in the area under study. Moreover, the Spearman rank difference correlation coefficient (ρ) method is applied on the ranking of ten digits, ‘0’ to ‘9’ and adopted in Turner’s method (1958) is also applied here and found (0.99) consistence with the Myers’ value. Finally, we find that the educational level of the population has an effect on the quality of age data.

Myers’ Index, Turner’s Method, and Spearman Rank Difference Correlation Coefficient (ρ)

[01] Ambannavar, J.P and Visaria, P. (1975). “Influence of Literacy and Education on the Quality of Age Returns.” Demography India, 4: 11-15, New Delhi. [02] Ewbank, D.C. (1981). Age Misreporting and Age-selective Underenumeration: Sources, Patterns and Consequences for Demographic Analysis, Report 4, Committee on Population and Demography, United States National Academy of Sciences, Washington. [03] Garrett, H.E. and Woodworth, R.S. (1961). Statistics in Psychology and Education, Longmans and Co. Inc., New York. [04] Gupta, S.K., Mukhopadhyay, B.K. and Pal, Jadab Kumar (2014). Myers’ Blended Method: An Alternative Approach, Journal of Scientific Research and Reports, Sciencedomain International, 3 (18), pp 2459-2465. [05] Jowett, A. John and Li, Yuan-Qing (1992). Age – Heaping: Contrasting Patterns from China, Geojournal, 28 ( 4), pp 427-442. [06] Kerr, D. (2003). “An Alternative Strategy for Evaluating and Generating Censal Estimates.” Genus, 59 (.3-4) pp 71-89. via Nomentana, 41,00161-Roma, Italy. [07] Mukhopadhyay, B.K. (2009). Digit Accuracies in Age Data for Developed Regions with Old Pattern of Digit Preference Error in Developing World, presented at the IUSSP conference at Marrakesh, Morocco. [08] Mukhopadhyay, B.K. (2006). Statistical Analysis in Evaluating The Demographic Data With Reference To Certain Special Characteristics, Ph.D Thesis, University Department of Statistics & Computer, T.M. Bhagalpur University, Bhagalpur-812 108, pp (i-xii) (1-126) (i-vii). [09] Mukhopadhyay, B.K. and Mukherjee, B.N. (1988). A study of Digit Preference and Quality of Age Data in Turkish Censuses, Genus, 40 (1-2), Italy. [10] Stockwell, E.G. and Wicks, J.W. (1974). Age heaping in Recent National Censuses, Social Biology, 21(2), pp163-167. [11] Stockwell, E.G. (1966). Patterns of Digit Preference and Avoidance in the Age Statistics of Some Recent National Censuses: a Test of the Turner Hypothesis, Eugenics Quarterly, 13(3), pp 205-208. [12] Srinivasan, K. (1998). Basic Demographic Techniques and Applications, Sage Publications, New Delhi.United Nations. (1983). Indirect techniques for demographic estimation, Manual X, UN Publication, New York, USA.United Nations. (1955). Methods of Appraisal of Quality of Basic Data for Population Estimates, Manual-II, Population Studies No. 3.