Description

Laboratory Statistics: Handbook of Formulas and Terms presents common strategies for comparing and evaluating numerical laboratory data. In particular, the text deals with the type of data and problems that laboratory scientists and students in analytical chemistry, clinical chemistry, epidemiology, and clinical research face on a daily basis. This book takes the mystery out of statistics and provides simple, hands-on instructions in the format of everyday formulas. As far as possible, spreadsheet shortcuts and functions are included, along with many simple worked examples. This book is a must-have guide to applied statistics in the lab that will result in improved experimental design and analysis.

Key Features

  • Comprehensive coverage of simple statistical concepts familiarizes the reader with formatted statistical expression
  • Simple, worked examples make formulas easy to use in real life
  • Spreadsheet functions demonstrate how to find immediate solutions to common problems
  • In-depth indexing and frequent use of synonyms facilitate the quick location of appropriate procedures

Readership

Analytical and clinical chemists, epidemiologists, researchers in all laboratory science disciplines, physicists, engineers, and students in these areas

Table of Contents

Acknowledgment

Introduction

Vocabulary and Concepts in Metrology

Some Notes on Nomenclature

Formulas

Abstract

Basics

Distributions of Data

Robust Estimators

Analysis of Variance

Difference Between Results; Student’s t-Tests

Nonparametric Comparisons

Regression

Correlation and Covariance

Comparing Quantities

Performance Characteristics

Estimation of Minimal Sample Size (Power Analysis)

Agreement Between Categorical Assessments (Kappa (κ)-Statistics)

Reference

Some Metrological Concepts

Abstract

Metrology, Accuracy, Trueness, and Precision

Uncertainty Concept and Uncertainty Budget

Miscellanea

Further Reading

Index

Details

No. of pages:
154
Language:
English
Copyright:
© 2014
Published:
Imprint:
Elsevier
Print ISBN:
9780124169715
Electronic ISBN:
9780124169739

About the author

Anders Kallner

Dr. Kallner studied general chemistry at the University of Stockholm and organic chemistry at the International Union of Pure and Applied Chemistry (IUPAC) Elections Royal Institute of Technology in Stockholm before graduating with a PhD in biochemistry from the Karolinska Institute in 1967. He later earned his MD at the same university and became Associate Professor of Clinical Chemistry at the Karolinska Institute. He has held positions in county, regional, and university hospitals. Although he retired from Karolinska University Hospital in 2005, Dr. Kallner retains professional assignments in the laboratory and international organizations. He has given more than 250 invited lectures and has contributed to more than 180 publications. Dr. Kallner has held numerous memberships and leadership roles on numerous international committees, including the International Organization for Standardization (ISO), the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC), and the IUPAC. Dr. Kallner has participated in the development of several CLSI Evaluation Protocols, and is currently the chair holder of the Subcommittee on Expression of Measurement Uncertainty in Laboratory Medicine (C51) and an active member of the CLSI Area Committee on Evaluation Protocols. He has chaired and participated in the development of a standard in metrology in ISO, CEN, and CLSI. Dr. Kallner’s scientific work has spanned a wide field ranging from organic synthesis and metabolism of cholesterol to epidemiological and metabolic studies of vitamin D. An interest in quality management and development of routines for quality assessment in the laboratory required studies in programming and statistics. Eventually, Dr. Kallner recognized the need for a compendium of useful statistical procedures and formulas that could easily be used in programming and understanding of statistical procedure.

Reviews

"…includes virtually every basic statistic a clinical scientist should need to comprehend in order to deal with most data sets, from exploring characteristics of the data to various simple linear regressions…If you have a reasonable grasp on the theory and methods of statistics already, this book will allow you to perform robust statistical analysis with a simple spreadsheet."--Chemistry International, July-August 2014