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  • 标题:Standardization of Sampling Technique for the Estimation of Guava Production in Himachal Pradesh
  • 本地全文:下载
  • 作者:Smriti Bansal ; P. K. Mahajan ; R. K. Gupta
  • 期刊名称:Current Journal of Applied Science and Technology
  • 印刷版ISSN:2457-1024
  • 出版年度:2022
  • 卷号:41
  • 期号:21
  • 页码:27-34
  • DOI:10.9734/cjast/2022/v41i2131752
  • 语种:English
  • 出版社:Sciencedomain International
  • 摘要:The present study focuses on standardization of sampling technique and comparison of sample allocation methods. The goal of stratification is to provide a better cross-section of the population in order to increase relative accuracy. For this purpose, Primary data on area and production of guava were obtained from 275 respondents of Himachal Pradesh through a well-designed and pre-tested survey approach. The optimum stratification points were found by using the auxiliary variable "area under guava" as the stratification variable. Four methods, namely, Equalization of strata totals, Equalization of cumulative √f(y)f(y) . Equalization of cumulative 1/2[r(y)+f(y)]1/2[r(y)+f(y)] and Equalization of cumulative 3√f(y)f(y)3 were used for the construction of approximate optimum strata boundaries for varying numbers of strata (L= 2,3,4,5) and sample sizes ni = 60, 90, 120. The sample was allocated to different strata according to proportional and Neyman allocation methods. The minimum estimate of the variance of of guava production and maximum gain in efficiency was found to be 0.004 and 418.11 percent respectively in Equalization of cumulative 3√f(y)f(y)3 rule for n =120 and L = 5 under Neymann allocation.
  • 关键词:Guava;stratification;stratified random sampling;optimum strata boundaries;neyman allocation;proportional allocation
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