Null Hypothesis Significance Testing and 'p' Values

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Bibliographic Details
Title: Null Hypothesis Significance Testing and 'p' Values
Language: English
Authors: Travers, Jason C. (ORCID 0000-0003-1956-3519), Cook, Bryan G. (ORCID 0000-0001-9294-0873), Cook, Lysandra
Source: Learning Disabilities Research & Practice. Nov 2017 32(4):208-215.
Availability: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 8
Publication Date: 2017
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Statistical Analysis, Special Education, Research, Hypothesis Testing, Misconceptions, Probability
DOI: 10.1111/ldrp.12147
ISSN: 0938-8982
Abstract: "p" values are commonly reported in quantitative research, but are often misunderstood and misinterpreted by research consumers. Our aim in this article is to provide special educators with guidance for appropriately interpreting "p" values, with the broader goal of improving research consumers' understanding and interpretation of research findings. Specifically, we discuss null hypothesis significance testing, describe what "p" values mean and how they are reported, describe some common misconceptions of "p" values, and provide two examples from the research literature to illustrate how "p" values are used in the field. Our take-home message is that "p" values indicate how likely study results are to occur if the null hypothesis is true, and that "p" values should be cautiously interpreted.
Abstractor: As Provided
Entry Date: 2017
Accession Number: EJ1159518
Database: ERIC
Description
Abstract:"p" values are commonly reported in quantitative research, but are often misunderstood and misinterpreted by research consumers. Our aim in this article is to provide special educators with guidance for appropriately interpreting "p" values, with the broader goal of improving research consumers' understanding and interpretation of research findings. Specifically, we discuss null hypothesis significance testing, describe what "p" values mean and how they are reported, describe some common misconceptions of "p" values, and provide two examples from the research literature to illustrate how "p" values are used in the field. Our take-home message is that "p" values indicate how likely study results are to occur if the null hypothesis is true, and that "p" values should be cautiously interpreted.
ISSN:0938-8982
DOI:10.1111/ldrp.12147