Abstract

This paper provides correct informations inflecting the present situation using the sample design in population that the National Statistical Office puts in operation of the mining and manufacturing industry statistical survey in 2006. This paper proposes new sampling design which is able to grasp business fluctuations and provide basic data for the rearing policy and management of the material industry and components industry. These sample design are the modified cut-off method and multivariate Neyman allocation using principal components and sampling method is the probability proportional systematic sampling.

Keywords

• Sample design;
• sampling error;
• modified cut-off method;
• PPS systematic sampling

• 표본설계;
• 표본 오차;
• 응용절사법;
• 확률비례계통추출법;

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References

1. 한국기계산업진흥회 (2007). <부품.소재 동향보고서>, 대한통계협회
2. Dalenius, T. and Hodges, J. L. (1959). The choice of stratification points, Skandinavisk Aktuarietidskrift, 40, 198-203
3. Hidiroglou, M. (1994). Sampling and estimation for establishment surveys: Stumbling blicks and progress, In Proceedings of the Section on Survey Research Methods, American Statistical Association, 153-162
4. Lavallee, P. and Hidiroglou, M. (1988). On the strati¯cation of skewed populations, Survey Methodology, 14, 33-43
5. Namkung, P., Byun, J. and Choi, J. (2007). Multivariate Neyman allocation using principle component analysis, ISI., 438
6. Sethi, V. K. (1963). A note on optimum stratification of populations for estimating the population means, Australian Journal of Statistics, 5, 20-33 https://doi.org/10.1111/j.1467-842X.1963.tb00134.x

Cited by

1. A Study on the Optimal Cut-off Point in the Cut-off Sampling Method vol.27, pp.3, 2014, https://doi.org/10.5351/KJAS.2014.27.3.501