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A Proposed Method for Choice of Sample Size without Pre-Defining Error

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DOI: 10.4236/jdaip.2015.34016    3,405 Downloads   3,777 Views  
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Sample size is very important in statistical research because it is not too small or too large. Given significant level α, the sample size is calculated based on the z-value and pre-defined error. Such error is defined based on the previous experiment or other study or it can be determined subjectively by specialist, which may cause incorrect estimation. Therefore, this research proposes an objective method to estimate the sample size without pre-defining the error. Given an available sample X = {X1, X2, ..., Xn}, the error is calculated via the iterative process in which sample X is re-sampled many times. Moreover, after the sample size is estimated completely, it can be used to collect a new sample in order to estimate new sample size and so on.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Nguyen, L. and Ho, H. (2015) A Proposed Method for Choice of Sample Size without Pre-Defining Error. Journal of Data Analysis and Information Processing, 3, 163-167. doi: 10.4236/jdaip.2015.34016.


[1] Montgomery, D.C. and Runger, G.C. (2003) Applied Statistics and Probability for Engineers. 3rd Edition, John Wiley & Son, Inc., Hoboken.
[2] Walpole, R.E., Myers, R.H., Myers, S.L. and Ye, K. (2007) Probability & Statistics for Engineers & Scientists. 9th Edition, Pearson Education, Inc.
[3] R Development Core Team (2010) R: A Language and Environment for Statistical Computing. R Foundation for Statistical computing, Vienna, Austria.

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