Gall's "Figuring Out the Importance of Research Article Review

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Gall's "Figuring out the Importance of Research Results: Statistical Significance versus

Practical Significance" is a good and somewhat indecisive viewpoint on statistical methods used to test the null hypothesis. Perhaps his observations prove to focus more in the importance of research results vs. The unimportance of research results in statistical significance. He goes back and forth on the significance which tells from Gall's viewpoint, that null hypothesis was repetitive due to the level of certainty and that accurate circumstances, for example a random sampling from a defined population, have been satisfied, but are limited. Levin's, "What if There Were No More Bickering About Statistical Significance Tests?" is again a well thought out, somewhat emotional, take on "those who advocate replacing statistical hypothesis testing with alternative data-analysis strategies." (Research in the Schools 1998)Download full Download Microsoft Word File
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TOPIC: Article Review on Gall's "Figuring Out the Importance of Research Assignment

In Gall's article, the kinds of problems where significance testing can be helpfully applied are in educational practice. "My concern in this paper is with the importance of research results for the improvement of educational practice." (Statistical Significance vs. Practical Significance of Research Results 2012) Levin's article focuses more on the lack of contextual simplicity in discussing statistical significance and uses an example of a hypothetical a and B. group treating six elderly patients. So in a way he's stating significance testing can be applied in almost anything related to a set number of tasks performed repetitively over time. Levin is also stating that significance testing cannot be applied is in educational research "Some of Nix and Barnette's assertions about statistical power and a study's publish ability are similarly misleading. "First, the authors state that the problem is of special concern in educational research, where ". . . effect sizes may be subtle, but at the same time, may indicate meritorious improvements in instruction and other class-room methods." (Research in the Schools 1998) Levin does not argue against the idea but rather the execution stating it was misleading due to the assumption of reliability based on sampling error, rather than reducing measurement error.

Levin doesn't discuss in depth about population or respondents, but rather how ineffectively the use of certain jargon is at conveying statistical significance. He states: "What a misrepresentation of the F-test and its operating characteristics! The error mean square (MSE) is an unbiased estimator of the population variance (o2) that is not systematically affected by sample size..." (Research in the Schools 1998) relying more on critiquing others work than pointing out anything of his own. He does use an example of at risk patients in a medical facility that perhaps can be seen as a population usually studied in business and organizational research. In fact most businesses study populations to see just how much risk these consumers or potential customers are for their business. Hospitals and schools also do this kind of research in at risk populations to develop the mean hypothesis in predicting reliability. Gall discusses the same thing in a school setting: "For example, suppose the research sample consists of fifth-graders and they are found tobe reading at the third-grade level on a particular standardized reading test. How well does the typical fifth-grader read, and how well does the typical third-grader read?" (Statistical Significance vs. Practical… [END OF PREVIEW] . . . READ MORE

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