Sample size and its role in Central Limit Theorem (CLT)

  • Mohammad Rafiqul Islam MNS, BRAC University, 66 Mohakhali, Dhaka, Bangladesh
Keywords: Inference, Precision, Sample size, Population and Sample, Confidence Interval (CI)


It is very important to determine the proper or accurate sample size in any field of research. Sometimes researchers cannot take the decision that how many numbers of individuals or objects will they select for their study purpose. Also, a set of survey data is used to verify that central limit theorem (CLT) for different sample sizes. From the data of 1348 students, we got the average weight for our population of BRAC University students is 62.62 kg with standard deviation 11.79 kg. We observed that our sample means became better estimators of the true population mean. In addition, the shape of the distribution became more Normal as the sample size increased. So it is concluded that our simulation results were consistent with the central limit theorem.


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How to Cite
Islam, M. R. (2018). Sample size and its role in Central Limit Theorem (CLT). International Journal of Physics & Mathematics, 1(1), 37-47.