Applications of inferential statistical methods in library and information science

Abstract

AbstractResearch 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 selection and control field. These findings help researchers better understand the statistical method orientation of library and information science studies and assist educators in the field to develop applicable quantitative research methodology courses.