1998Unpublished venueRequires access

The Role of Statistical Significance Testing In Educational Research

James E. McLean, James M. Ernest

Open publisher page 106 citations

Abstract

The research methodology literature in recent years has included a full frontal assault on statistical significance testing. The purpose of this paper is to promote the position that, while significance testing as the sole basis for result interpretation is a fundamentally flawed practice, significance tests can be useful as one of several elements in a comprehensive interpretation of data. Specifically, statistical significance is but one of three criteria that must be demonstrated to establish a position empirically. Statistical significance merely provides evidence that an event did not happen by chance. However, it provides no information about the meaningfulness (practical significance) of an event or if the result is replicable. Thus, we support other researchers who recommend that statistical significance testing must be accompanied by judgments of the event’s practical significance and replicability. The research methodology literature in recent years has included a full frontal assault on statistical significance testing. An entire edition of a recent issue of Experimental Education (Thompson, 1993b) explored this controversy. There are some who recommend the total abandonment of statistical significance testing as a research methodology option, while others choose to

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What this paper is about

The research methodology literature in recent years has included a full frontal assault on statistical significance testing. The purpose of this paper is to promote the position that, while significance testing as the sole basis for result interpretation is a fundamentally flawed practice, significance tests can be useful as one of several elements in a comprehensive interpretation of data. Specifically, statistical significance is but one of three criteria that must be demonstrated to establish a position empirically. Statistical significance merely provides evidence that an event did not happen by chance. However, it provides no information about the meaningfulness (practical significance) of an event or if the result is replicable. Thus, we support other researchers who recommend that statistical significance testing must be accompanied by judgments of the event’s practical significance and replicability. The research methodology literature in recent years has included a full frontal assault on statistical significance testing. An entire edition of a recent issue of Experimental Education (Thompson, 1993b) explored this controversy. There are some who recommend the total abandonment of statistical significance testing as a research methodology option, while others choose to

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Available abstract

The research methodology literature in recent years has included a full frontal assault on statistical significance testing. The purpose of this paper is to promote the position that, while significance testing as the sole basis for result interpretation is a fundamentally flawed practice, significance tests can be useful as one of several elements in a comprehensive interpretation of data. Specifically, statistical significance is but one of three criteria that must be demonstrated to establish a position empirically. Statistical significance merely provides evidence that an event did not happen by chance. However, it provides no information about the meaningfulness (practical significance) of an event or if the result is replicable. Thus, we support other researchers who recommend that statistical significance testing must be accompanied by judgments of the event’s practical significance and replicability. The research methodology literature in recent years has included a full frontal assault on statistical significance testing. An entire edition of a recent issue of Experimental Education (Thompson, 1993b) explored this controversy. There are some who recommend the total abandonment of statistical significance testing as a research methodology option, while others choose to

Key concepts: Statistical significance, Statistical hypothesis testing, Significance testing, Psychology, Test (biology), Interpretation (philosophy), Event (particle physics), Position (finance)

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