Applications of inferential statistical methods in library and information science
Open accessAbstract
Research methods play an extremely important role in studies. Statistical methods are fundamental and vital for quantitative research. The authors of this paper investigated the research papers that used statistical methods including parametric inferential statistical methods, nonparametric inferential statistical methods, predictive statistical correlation methods, and predictive statistical regression methods in library and information science and examined the connections and interactions between statistical methods and their application areas including information creation, information selection and control, information organization, information retrieval, information dissemination, and information use. Both an inferential statistical method and graphic clustering visualization method were employed to explore the relationships between statistical methods and application areas and reveal the hidden interaction patterns. As a result, 1821 research papers employing statistical methods were identified among the papers published in six major library and information science journals from 1999 to 2017. The findings showed that application areas affected the types of statistical methods utilized. Studies in information organization and information retrieval tended to employ parametric and nonparametric inferential methods, while correlation and regression methods were applied more in studies in information use, information dissemination, information creation, and information selec…
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The use of inferential statistics in the library science literature is increasing.
“Given the continued pressure on libraries to quantitavely demonstrate their value and contribution to students' learning outcomes, and the increasing use of inferential statistics in the library science literature (Wallace 1985; Zhang, Wang, and Zhao 2017; Zhang et al. 2018)”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Zhang et al. 2018
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Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies
Robertshaw, M. B., & Asher, A. (2019) · Library Trends · doi:10.1353/lib.2019.0031 · Cited by 32 · see citing works
- Authors
- Zhang, J., Wang, Y., Zhao, Y., & Cai, X.
- Affiliations
- University of Wisconsin–Milwaukee (US)
- Corresponding author
- Zhao, Yuehua
- Venue
- Data and Information Management
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 2
- Issue
- 2
- Pages
- 103-120
- ISSN
- 2543-9251 (ISSN-L)
- OpenAlex
- W2887187944
- Cited by
- 21
- References
- 0
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 4 · 2023: 1 · 2022: 5 · 2021: 5 · 2020: 2 · 2019: 1
- FWCI
- 1.53
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Data and Information Management (publishedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Physical Sciences › Computer Science › Information Systems › Library Science and Information
- Physical Sciences › Computer Science › Information Systems › Information Science and Libraries
- Keywords
- library and information science research, parametric statistics, nonparametric statistics, correlation analysis, regression analysis, information organization, information retrieval, information use, information dissemination, information creation, research methods course
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