06 May 2018

Data Science: Precision (Definitions)

"Precision is the ‘spread’ or variability of repeated measures of the same value." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)

"Defines the variation in repeated measurements of the same item. There are two major ways to measure precision - repeatability and reproducibility." (Lynne Hambleton, "Treasure Chest of Six Sigma Growth Methods, Tools, and Best Practices", 2007)

"An inherent quality characteristic that is a measure of an attribute’s having the right level of granularity in the data values." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"Largest likely estimation error, measured by MOE." (Geoff Cumming, "Understanding The New Statistics", 2013)

"The level of detail included in information, such as the number of decimal places in a number, the number of pixels/inch in an image (resolution), or other measure reflecting how closely information is observed. Not to be confused with Accuracy defined elsewhere in this glossary." (Kenneth A Shaw, "Integrated Management of Processes and Information", 2013)

"Within the quality management system, precision is a measure of exactness. |" (For Dummies, "PMP Certification All-in-One For Dummies, 2nd Ed.", 2013)

"Precision easures the accuracy of a result set, that is, how many of the retrieved resources for a query are relevant." (Robert J Glushko, "The Discipline of Organizing: Professional Edition, 4th Ed", 2016)


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Koeln, NRW, Germany
IT Professional with more than 24 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.