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Research Guides@Tufts

Statistics and Probability as a Discipline: Gray Literature

What is Gray Literature?

Gray (or Grey) literature is a term used in scientific and research communities for certain types of research-oriented documents.  It commonly refers to materials other than journals and monographs that are not usually published by commercial publishers.  Gray literature includes technical reports, standards, patents, white papers, protocols, and, increasingly, GIS and data sets.   With the exception of U.S. patents, much of this literature - particularly that published before the era of digitization - is difficult to locate as it has not been systematically collected or cataloged by libraries and repositories. 

The U.S. Government is a major publisher of gray literature and in recent years has been taking advantage of the internet to make its publications more easily available.  Professional associations, standards organizations, and "working groups" focusing on particular subjects also contribute to the gray literature.  A summary of the various document types which constitute gray literature is available from GreyNet, an organization dedicated to tracking gray literature.

For the study of statistics and probability, gray literature is an important source of information on both methodologies and applications of these subjects.

Patents

Patents -- government-issued documents which protect inventions - contain information on statistical tools and approaches.  Whether statistical methods and other forms of mathematics can or should be patentable is a subject of debate.

Technical Reports

Technical reports provided detailed information on research processes, results, and observations, all of which can use or address statistics.  They often provide more extensive details than do journal articles or other sources.  Many are published by government agencies, standard organizations, and other non-commercial publishers.

Technical Standards

Technical standards help establish norms and standards for measurement, performance, quality, and other areas where conformity is important.  Many standards embed applications of statistical methods while others set standards for such methods.