Introduction To Statistical Analysis Of Laboratory Data
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Introduction to Statistical Analysis of Laboratory Data by Alfred Bartolucci,Karan P. Singh,Sejong Bae Pdf
Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process Introduces terminology used in many applications such as the interpretation of assay design and validation as well as “fit for purpose” procedures including real world examples Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions
This book deals with the statistical treatment of experimental data. It is also meant for those who are entirely new to the field of statistics and probability calculus, and those who wish to obtain rigorous estimates of the uncertainties associated with the experimental results of any discipline, such as meteorology, engineering, physics, chemistry and the life sciences. To understand the text, only a basic understanding of differential calculus is required. As an innovative teaching approach, simple laboratory class experiments are used as the basis for developing a detailed statistical analysis. This is done by directly using the students' logbooks without re-elaboration. The approach is profitable and can be easily pursued by the layman. People have, in the past, been confused by the many statistical definitions, formulae and assumptions. This book tries to avoid any arbitrary definition by using the recently introduced ISO directives. All the concepts, parameters and test variables forthe modern,treatment of the experimental data are included. Among them are the error, the uncertainty and its estimate, the distribution functions and the associated parameters. Every concept is always associated with a simple experimental situation and the data analysis is performed in numerical detail. For completeness, the correlation of the uncertainties with the error matrix is treated in greater detail. All the tests of hypotheses are presented. They are introduced from simple arguments and developed up to the analytical details. The applications of the tests to the fitting of experimental curves of the c(2), t and F tests, as well as the one most often used in the life sciences, theANOVA, are shown.
Data Analysis for Chemistry by D. Brynn Hibbert,Professor of Analytical Chemistry D Brynn Hibbert,J. Justin Gooding Pdf
Annotation. Definitions, Questions, and Useful Functions: Where to Find Things and What To Do1. Introduction2. Describing Data3. Hypothesis Testing4. Analysis of Variance5. Calibration.
Introduction to Statistical Methods in Pathology by Amir Momeni,Matthew Pincus,Jenny Libien Pdf
This text provides a comprehensive and practical review of the main statistical methods in pathology and laboratory medicine. It introduces statistical concepts used in pathology and laboratory medicine. The information provided is relevant to pathologists both for their day to day clinical practice as well as in their research and scholarly activities. The text will begins by explaining the fundamentals concepts in statistics. In the later sections, these fundamental concepts are expanded and unique applications of statistical methods in pathology and laboratory medicine practice are introduced. Other sections of the text explain research methodology in pathology covering a broad range of topics from study design to analysis of data. Finally, data-heavy novel concepts that are emerging in pathology and pathology research are presented such as molecular pathology and pathology informatics. Introduction to Statistical Methods in Pathology will be of great value for pathologists, pathology residents, basic and translational researchers, laboratory managers and medical students.
Statistical Analysis of Laboratory Data by Stanley N. Deming Pdf
This first volume in a projected three-volume series provides the reader with a deep understanding of the basic theory required to carry out the statistical analysis of laboratory data. The approach is visual and conversational -- slow, steady, and effective. By the end of the book, the reader will be able to carry out one-sample statistical tests with self assurance and certainty. The books in this series are highly recommended as companion volumes for students beginning their first studies of statistics, whether in academia or industry -- the individual volumes present important statistical concepts with more clarity, depth, and breadth than are found in typical beginning textbooks.
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. 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
Using a truly accessible and reader-friendly approach, Introduction to Statistics: Fundamental Concepts and Procedures of Data Analysis, by Howard M. Reid, redefines the way statistics can be taught and learned. Unlike other books that merely focus on procedures, Reid’s approach balances development of critical thinking skills with application of those skills to contemporary statistical analysis. He goes beyond simply presenting techniques by focusing on the key concepts readers need to master in order to ensure their long-term success. Indeed, this exciting new book offers the perfect foundation upon which readers can build as their studies and careers progress to more advanced forms of statistics. Keeping computational challenges to a minimum, Reid shows readers not only how to conduct a variety of commonly used statistical procedures, but also when each procedure should be utilized and how they are related. Following a review of descriptive statistics, he begins his discussion of inferential statistics with a two-chapter examination of the Chi Square test to introduce students to hypothesis testing, the importance of determining effect size, and the need for post hoc tests. When more complex procedures related to interval/ratio data are covered, students already have a solid understanding of the foundational concepts involved. Exploring challenging topics in an engaging and easy-to-follow manner, Reid builds concepts logically and supports learning through robust pedagogical tools, the use of SPSS, numerous examples, historical quotations, insightful questions, and helpful progress checks.
Statistics for the Quality Control Chemistry Laboratory by Eamonn Mullins Pdf
Statistical methods are essential tools for analysts, particularly those working in Quality Control Laboratories. This book provides a sound introduction to their use in analytical chemistry, without requiring a strong mathematical background. It emphasises simple graphical methods of data analysis, such as control charts, which are also a fundamental requirement in laboratory accreditation. A large part of the book is concerned with the design and analysis of laboratory experiments, including sample size determination. Practical case studies and many real databases from both QC laboratories and the research literature, are used to illustrate the ideas in action. The aim of Statistics for the Quality Control Chemistry Laboratory is to give the reader a strong grasp of the concept of statistical variation in laboratory data and of the value of simple statistical ideas ad methods in thinking about and manipulation such data, It will be invaluable to analysts working in QC laboratories in industry, hospitals and public health, and will also be welcomed as a textbook for aspiring analysts in colleges and universities.
Clinical Investigation and Statistics in Laboratory Medicine by Richard G. Jones,R. Brian Payne Pdf
This text is designed for laboratory workers and clinicians but should also be useful for other healthcare workers. The authors assume that the reader has access to a computer with statistical software for inspection and analysis of data. The book has four main parts. Chapter 1 describes the different kinds of data and statistical analyses that can be applied to them. Topics include how to assess the shape of distributions, how to transform data, when to use parametric and non-parametric tests, and how to check data input and deal with outliers. Chapter 2 deals with the inaccuracy, imprecision, detection limits, analytical goals and other aspects of analytical methods used in laboratory medicine, and explains how to compare both quantitative and qualitative analytical methods.
Statistical Methods in Laboratory Medicine by P. W. Strike Pdf
Statistical Methods in Laboratory Medicine focuses on the application of statistics in laboratory medicine. The book first ponders on quantitative and random variables, exploratory data analysis (EDA), probability, and probability distributions. Discussions focus on negative binomial distribution, non-random distributions, binomial distribution, fitting the binomial model to sample data, conditional probability and statistical independence, rules of probability, and Bayes' theorem. The text then examines inference, regression, and measurement and control. Topics cover analytical goals for assay precision, estimating the error variance components, indirect structural assays, functional assays, bivariate regression model, and least-squares estimates of the functional relation parameters. The manuscript takes a look at assay method comparison studies, multivariate analysis, forecasting and control, and test interpretation. Concerns include time series structure and terminology, polynomial regression, assessing the performance of the classification rule, quantitative screening tests, sample correlation coefficient, and computer assisted diagnosis. The book is a dependable reference for medical experts and statisticians interested in the employment of statistics in laboratory medicine.
An Introduction to Statistical Analysis in Research, Optimized Edition by Kathleen F. Weaver,Vanessa C. Morales,Sarah L. Dunn,Kanya Godde,Pablo F. Weaver Pdf
Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS®, Excel®, and Numbers® output An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages including R, SPSS®, Excel®, and Numbers®. Specific emphasis is on the practical application of statistics in the biological and life sciences, while enhancing reader skills in identifying the research questions and testable hypotheses, determining the appropriate experimental methodology and statistical analyses, processing data, and reporting the research outcomes. In addition, this book: • Aims to develop readers’ skills including how to report research outcomes, determine the appropriate experimental methodology and statistical analysis, and identify the needed research questions and testable hypotheses • Includes pedagogical elements throughout that enhance the overall learning experience including case studies and tutorials, all in an effort to gain full comprehension of designing an experiment, considering biases and uncontrolled variables, analyzing data, and applying the appropriate statistical application with valid justification • Fills the gap between theoretically driven, mathematically heavy texts and introductory, step-by-step type books while preparing readers with the programming skills needed to carry out basic statistical tests, build support figures, and interpret the results • Provides a companion website that features related R, SPSS, Excel, and Numbers data sets, sample PowerPoint® lecture slides, end of the chapter review questions, software video tutorials that highlight basic statistical concepts, and a student workbook and instructor manual An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences is an ideal textbook for upper-undergraduate and graduate-level courses in research methods, biostatistics, statistics, biology, kinesiology, sports science and medicine, health and physical education, medicine, and nutrition. The book is also appropriate as a reference for researchers and professionals in the fields of anthropology, sports research, sports science, and physical education. KATHLEEN F. WEAVER, PhD, is Associate Dean of Learning, Innovation, and Teaching and Professor in the Department of Biology at the University of La Verne. The author of numerous journal articles, she received her PhD in Ecology and Evolutionary Biology from the University of Colorado. VANESSA C. MORALES, BS, is Assistant Director of the Academic Success Center at the University of La Verne. SARAH L. DUNN, PhD, is Associate Professor in the Department of Kinesiology at the University of La Verne and is Director of Research and Sponsored Programs. She has authored numerous journal articles and received her PhD in Health and Exercise Science from the University of New South Wales. KANYA GODDE, PhD, is Assistant Professor in the Department of Anthropology and is Director/Chair of Institutional Review Board at the University of La Verne. The author of numerous j
Basic Statistics for Laboratories by William D. Kelley,Thomas A. Ratliff,Charles Nenadic Pdf
Marketing and regulatory pressures are driving laboratories to adopt statistically valid quality control or quality assurance systems. For the laboratory professional who’s unfamiliar with the statistical tools used in laboratory quality control, Basic Statistics for Laboratories offers guidance to employing basic statistical controls or reports required by regulatory or accrediting organizations, as well as statistical methods which may otherwise be useful in the lab. The book explains, in basic terms, 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. There is step-by-step guidance to method development, validation, comparison of test methods, and quality control for even small samples, without the use of mathematics beyond the high school level. Tests for the significance of differences, presented in "cookbook" format solutions, make it easy for lab professionals to plug in their own data and use tables. You’ll also find exclusive coverage of the problems of asbestos counting laboratories. In addition, the volume presents simple solutions to other problems involving data handling and interpretation, such as the treatment of outliers and how to deal with single or rarely encountered samples. For analysts, test engineers, and laboratory technicians in medical, pathological, environmental, industrial hygiene, and forensic laboratories, Basic Statistics for Laboratories is a timely and essential reference.
