Sample size and its role in Central Limit Theorem (CLT)
Keywords:
Inference, Precision, Sample size, Population and Sample, Confidence Interval (CI)Abstract
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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References
Apedoe, X. S., & Reeves, T. C. (2006). Inquiry-based learning and digital libraries in undergraduate science education. Journal of science education and technology, 15(5-6), 321-330.
Arsham, H. (1998). Algorithms for sensitivity information in discrete-event systems simulation. Simulation Practice and Theory, 6(1), 1-22.
Barlett, J. E., Kotrlik, J. W., & Higgins, C. C. (2001). Organizational research: Determining appropriate sample size in survey research. Information technology, learning, and performance journal, 19(1), 43.
Cochran, W. G. (2007). Sampling techniques. John Wiley & Sons.
Cox, D. R. (1958). Some problems connected with statistical inference. The Annals of Mathematical Statistics, 29(2), 357-372.
De Calderero, R. P., Panchana, M. J. C., Lectong, D. M., & Hernández, E. H. O. (2018). Use of Concrete Debris. International Journal of Physical Sciences and Engineering (IJPSE), 2(1), 1-12.
Eckhardt, K. W., & Ermann, M. D. (1977). Social research methods: Perspective, theory, and analysis. Random House (NY).
Fleishman, A. I. (1978). A method for simulating non-normal distributions. Psychometrika, 43(4), 521-532.
González, A. E. D., Arauz, W. M. S., Gámez, M. R., & Alava, L. A. C. (2017). Photovoltaic Energy to Face an Earthquake. International Journal of Physical Sciences and Engineering (IJPSE), 1(3), 19-30.
Holton, E. (1997). Human resource development research handbook.
Israel, G. D. (1992). Determining sample size.
Israel, G. D. (1992). Sampling the evidence of extension program impact. University of Florida Cooperative Extension Service, Institute of Food and Agriculture Sciences, EDIS.
Johnson, P. O. (1959). Development of the sample survey as a scientific methodology. The Journal of Experimental Education, 27(3), 167-176.
Kish, L. (1965). Survey sampling.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(3), 607-610.
Kusumayanti, G. D., & Dewantari, N. M. (2017). The Influence of Low Purine Diet and Physical Activity on Changing of Uric Acid Levels in Hyperuricemia. International Journal of Health Sciences (IJHS), 1(3), 1-9.
Marshall, M. N. (1996). Sampling for qualitative research. Family practice, 13(6), 522-526.
Meehan, M. L., Cowley, K. S., Finch, N. L., Chadwick, K. L., Ermolov, L. D., & Riffle, M. J. S. (2004). Special Strategies Observation System-Revised: A Useful Tool for Educational Research and Evaluation. American Educational Research Association.
Micceri, T. (1989). The unicorn, the normal curve, and other improbable creatures. Psychological bulletin, 105(1), 156.
Spaeth, J. L. (1992). Perils and pitfalls of survey research. Allerton Park Institute (33rd: 1991).
Stonehouse, J. M., & Forrester, G. J. (1998). Robustness of the t and U tests under combined assumption violations. Journal of Applied Statistics, 25(1), 63-74.
Sudman, S. (1976). Applied sampling (No. 04; HN29, S8.). New York: Academic Press.
Thompson, B. (2003). Guidelines for authors reporting score reliability estimates. Score reliability: Contemporary thinking on reliability issues, 91-102.
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