Pub. Date:
Wiley, John & Sons, Incorporated
Basic Statistics for Laboratories: A Primer for Laboratory Workers

Basic Statistics for Laboratories: A Primer for Laboratory Workers


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Basic Statistics for Laboratories: A Primer for Laboratory Workers

Basic Statistics for Laboratories offers guidance to employing basic statistical controls or reports required by regulatory or accrediting organizations. The book explains how to set up, maintain, and interpret control charts and other commonly used laboratory statistical tools, and explains their value to the user. Every technique is delivered in its simplest, most basic form.

Product Details

ISBN-13: 9780442004569
Publisher: Wiley, John & Sons, Incorporated
Publication date: 01/28/1991
Pages: 175
Product dimensions: 6.24(w) x 9.27(h) x 0.65(d)

About the Author

About the Authors William D. Kelley has been an advisor for several American Society for Testing and Material Committees in the areas of statistics and laboratory quality control. Through his involvement with NIOSH and AIHA, he has developed accreditation procedures and several training courses for industrial hygiene laboratories. Thomas A. Ratliff, Jr. is a consultant in the field of industrial quality control for the EPA, NIOSH, and the Mine Safety and Health Administration. He is also a senior member of the American Society for Quality Control, a certified quality engineer and auditor, and a registered professional engineer in Quality Engineering. Charles M. Nenadic is the president of Consolidated Environmental Service, Inc. and has developed several courses in the areas of Industrial Hygiene for NIOSH. He is both a Registered Engineer and a member of the state bar of Kentucky.

Table of Contents

Distribution and Variability of Sampling Data.
Measuring Variability.
Tests of Normality.
Control Charts.
Special Situation Control Charts.
Statistical Tools for the Laboratory.
Sampling Plans.
Correlation and Regression.
Introduction to Outlying Observations.
Single Outliers.
Multiple Outliers.
Outliers Appearing in Continuous Data Sets.
Statistical Quality Control for Asbestos Counting.
Nonroutine Quality Control Procedures.

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