ERIC Number: ED393939
Record Type: RIE
Publication Date: 1995-Nov-9
Reference Count: N/A
Understanding the Sampling Distribution and Its Use in Testing Statistical Significance.
Breunig, Nancy A.
Despite the increasing criticism of statistical significance testing by researchers, particularly in the publication of the 1994 American Psychological Association's style manual, statistical significance test results are still popular in journal articles. For this reason, it remains important to understand the logic of inferential statistics. A fundamental concept in inferential statistics is the sampling distribution. This paper explains the sampling distribution and the Central Limit Theorem and their role in statistical significance testing. Included in the discussion is a demonstration of how computer applications can be used to teach students about the sampling distribution. The paper concludes with an example of hypothesis testing and an explanation of how the standard deviation of the sampling distribution is either calculated based on statistical assumptions or is empirically estimated using logics such as the "bootstrap." These concepts are illustrated through the use of hand generated and computer examples. An appendix displays five computer screens designed to teach these topics. (Contains 1 table, 4 figures, and 20 references.) (Author/SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Authoring Institution: N/A
Identifiers: Bootstrap Methods; Central Limit Theorem
Note: Paper presented at the Annual Meeting of the Mid-South Educational Research Association (Biloxi, MS, November 1995).