The Central Limit Theorem in the Sociology Classroom: A Constructivist Approach

Main Article Content

Brigitte Helene Bechtold

Abstract

To undergraduate students of sociology, and who are required to take at least one course in research methods, understanding of the CLT requires the successful negotiation of a number of hurdles, lack of training in mathematics in general and mathematical statistics in particular, and a sociological aversion to the “bell curve” or normal distribution. This paper critiques the “sweetening” approaches to conduct experiments that construct the Central Limit Theorem in the classroom. It proceeds to outline a simple type of experiment based on a discrete rectangular population distribution, and offers a proof, understandable to sociology undergraduates, of how a discrete rectangular population distribution gives rise to a continuous sampling distribution.

Downloads

Download data is not yet available.

Article Details

How to Cite
Bechtold, B. (2018). The Central Limit Theorem in the Sociology Classroom: A Constructivist Approach. International Journal for Innovation Education and Research, 6(6), 57-66. https://doi.org/10.31686/ijier.Vol6.Iss6.1058
Section
Articles
Author Biography

Brigitte Helene Bechtold, Central Michigan University

Professor of Sociology at Central Michigan University. 

Ph.D. in Economics from the University of Pennsylvania.

References

Bechtold, B. H. and Johnson, R. H. (1989), Statistics for Business and Economics. Boston: PWS-Kent.

Dambolena, I. G. (1986), “Using Simulation in Statistics Courses,” Collegiate Microcomputer 4: 339-344.

Goertzel, T. and Fashing, J. (1981), “The Myth of the Normal Curve: A Theoretical Critique and Examination of its Role in Teaching and Research,” Humanity and Society 5: 14-31.

Grinstead, C. M., and Snell, J. L. (1997), Introduction to Probability. 2nd rev. ed. Providence RI: American Mathematical Society.

Kennedy, K., Olinskey, A. and Schumacher, P. (1990), “Using Simulation as an Integrated Teaching Tool in the Mathematics Classroom,” Education 111: 275-296.

Landau, D. and Lazarsfeld, P. F. (1968), “Adolphe Quetelet,” In International Encyclopedia of the Social Sciences. Vol 13. New York: Macmillan and Free Press.

Mills, J. D. (2002), “Using Computer Simulation Methods to teach Statistics: A Review of the Literature,” Journal of Statistics Education, 10 (n.p.). Available online at http://www.amstat.org/ publications/jse/v10n1/mills.html.

Ng, V. M., and Wong, K. Y. (1999), “Using simulation on the Internet to teach Statistics,” The Mathematics Teacher 92: 729-733.

Paret, M. and Martz, E. (2008), “Sweetening Statistics with Minitab 16,” Minitab News, August. Online at http://www.minitab.com/uploadedFiles/Content/Academic/sweetening_statistics.pdf.

West, R. W. and Ogden, R. T. (1998), “Interactive Demonstrations for Statistics Education on the World Wide Web,” Journal of Statistics Education, 6 (n.p.). Available online at http://www. amstat.org/publications/jse/v6n3/west.html.

Wicklin, R. (2014), Fundamental Theorems of Mathematics and Statistics. Online at http:// www.blogs.sas.com/content/iml/2014/02/12/fundamental-theorems-of-mathematics-and-statistics/ (n.p.).

Yu, C. H., Behrens, J. T., and Anthony, S. (1995), “Identification of Misconceptions in the Central Limit Theorem and Related Concepts and Evaluation of Computer Media as a Remedial Tool,” ERIC Document Reproduction Service No. 395 989. New Orleans LA.