[PDF] Essential Statistical Concepts For The Quality Professional eBook

Author : D. H. Stamatis
Publisher : CRC Press
Page : 512 pages
File Size : 48,55 MB
Release : 2012-05-02
Category : Business & Economics
ISBN : 1439894574

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The essence of any root cause analysis in our modern quality thinking is to go beyond the actual problem. This means not only do we have to fix the problem at hand but we also have to identify why the failure occurred and what was the opportunity to apply the appropriate knowledge to avoid the problem in the future. Essential Statistical Concepts for the Quality Professional offers a new non-technical statistical approach to quality for effective improvement and productivity by focusing on very specific and fundamental methodologies and tools for the future. Written by an expert with more than 30 years of experience in management, quality training, and consulting, the book examines the fundamentals of statistical understanding, and by doing so demonstrates the importance of using statistics in the decision making process. The author points out pitfalls to keep in mind when undertaking an experiment for improvement and explains how to use statistics in improvement endeavors. He discusses data interpretation, common tests and confidence intervals, and how to plan experiments for improvement. The book expands the notion of experimentation by dealing with mathematical models such as regression to optimize the improvement and understand the relationship between several factors. It emphasizes the need for sampling and introduces specific techniques to make sure accuracy and precision of the data is appropriate and applicable for the study at hand. The author’s approach is somewhat new and unique; however, he details tools and methodologies that can be used to evaluate the system for prevention. These tools and methodologies focus on structured, repeatable processes that can be instrumental in finding real, fixable causes of the human errors and equipment failures that lead to quality issues.

Author : Peter Bruce
Publisher : "O'Reilly Media, Inc."
Page : 322 pages
File Size : 37,2 MB
Release : 2017-05-10
Category : Computers
ISBN : 1491952911

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Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Author : Nadia Russ
Publisher : NeoPopRealism PRESS
Page : 47 pages
File Size : 44,65 MB
Release : 2015-08-07
Category : Literary Criticism
ISBN :

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NeoPopRealism Journal and Wonderpedia founded by Nadia Russ in 2007 (N.J.) and 2008 (W.). Wonderpedia is dedicated to books published all over the globe after year 2000, offering the books' reviews.

Author : Per Winkel
Publisher : John Wiley & Sons
Page : 280 pages
File Size : 47,27 MB
Release : 2007-06-13
Category : Mathematics
ISBN : 9780470515891

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The promotion of standards and guidelines to advance quality assurance and control is an integral part of the health care sector. Quantitative methods are needed to monitor, control and improve the quality of medical processes. Statistical Development of Quality in Medicine presents the statistical concepts behind the application of industrial quality control methods. Filled with numerous case studies and worked examples, the text enables the reader to choose the relevant control chart, to critically apply it, improve it if necessary, and monitor its stability. Furthermore, the reader is provided with the necessary background to critically assess the literature on the application of control charts and risk adjustment and to apply the findings. Contains a user-friendly introduction, setting out the necessary statistical concepts used in the field. Uses numerous real-life case studies from the literature and the authors’ own research as the backbone of the text. Provides a supplementary website featuring problems and answers drawn from the book, alongside examples in Statgraphics. The accessible style of Statistical Development of in Clinical Medicine invites a large readership. It is primarily aimed at health care officials, and personnel responsible for developing and controlling the quality of health care services. However, it is also ideal for statisticians working with health care problems, diagnostic and pharmaceutical companies, and graduate students of quality control.

Author : Debbie L. Hahs-Vaughn
Publisher : Routledge
Page : 534 pages
File Size : 44,57 MB
Release : 2013-06-19
Category : Psychology
ISBN : 113649006X

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Statistical Concepts consists of the last 9 chapters of An Introduction to Statistical Concepts, 3rd ed. Designed for the second course in statistics, it is one of the few texts that focuses just on intermediate statistics. The book highlights how statistics work and what they mean to better prepare students to analyze their own data and interpret SPSS and research results. As such it offers more coverage of non-parametric procedures used when standard assumptions are violated since these methods are more frequently encountered when working with real data. Determining appropriate sample sizes is emphasized throughout. Only crucial equations are included. The new edition features: New co-author, Debbie L. Hahs-Vaughn, the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award. A new chapter on logistic regression models for today's more complex methodologies. Much more on computing confidence intervals and conducting power analyses using G*Power. All new SPSS version 19 screenshots to help navigate through the program and annotated output to assist in the interpretation of results. Sections on how to write-up statistical results in APA format and new templates for writing research questions. New learning tools including chapter-opening vignettes, outlines, a list of key concepts, "Stop and Think" boxes, and many more examples, tables, and figures. More tables of assumptions and the effects of their violation including how to test them in SPSS. 33% new conceptual, computational, and all new interpretative problems. A website with Power Points, answers to the even-numbered problems, detailed solutions to the odd-numbered problems, and test items for instructors, and for students the chapter outlines, key concepts, and datasets. Each chapter begins with an outline, a list of key concepts, and a research vignette related to the concepts. Realistic examples from education and the behavioral sciences illustrate those concepts. Each example examines the procedures and assumptions and provides tips for how to run SPSS and develop an APA style write-up. Tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. Each chapter includes computational, conceptual, and interpretive problems. Answers to the odd-numbered problems are provided. The SPSS data sets that correspond to the book’s examples and problems are available on the web. The book covers basic and advanced analysis of variance models and topics not dealt with in other texts such as robust methods, multiple comparison and non-parametric procedures, and multiple and logistic regression models. Intended for courses in intermediate statistics and/or statistics II taught in education and/or the behavioral sciences, predominantly at the master's or doctoral level. Knowledge of introductory statistics is assumed.

Author : Peter Bruce
Publisher : "O'Reilly Media, Inc."
Page : 317 pages
File Size : 50,75 MB
Release : 2017-05-10
Category : Computers
ISBN : 1491952938

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Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Author : Cheryl Ann Willard
Publisher : Routledge
Page : 367 pages
File Size : 36,24 MB
Release : 2020-02-27
Category : Psychology
ISBN : 0429523157

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Statistical Methods: An Introduction to Basic Statistical Concepts and Analysis, Second Edition is a textbook designed for students with no prior training in statistics. It provides a solid background of the core statistical concepts taught in most introductory statistics textbooks. Mathematical proofs are deemphasized in favor of careful explanations of statistical constructs. The text begins with coverage of descriptive statistics such as measures of central tendency and variability, then moves on to inferential statistics. Transitional chapters on z-scores, probability, and sampling distributions pave the way to understanding the logic of hypothesis testing and the inferential tests that follow. Hypothesis testing is taught through a four-step process. These same four steps are used throughout the text for the other statistical tests presented including t tests, one- and two-way ANOVAs, chi-square, and correlation. A chapter on nonparametric tests is also provided as an alternative when the requirements cannot be met for parametric tests. Because the same logical framework and sequential steps are used throughout the text, a consistency is provided that allows students to gradually master the concepts. Their learning is enhanced further with the inclusion of "thought questions" and practice problems integrated throughout the chapters. New to the second edition: Chapters on factorial analysis of variance and non-parametric techniques for all data Additional and updated chapter exercises for students to test and demonstrate their learning Full instructor resources: test bank questions, Powerpoint slides, and an Instructor Manual

Author : Chang W. Kang
Publisher : John Wiley & Sons
Page : 198 pages
File Size : 34,82 MB
Release : 2012-08-29
Category : Technology & Engineering
ISBN : 1118491491

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This book is an introductory book on improving the quality of a process or a system, primarily through the technique of statistical process control (SPC). There are numerous technical manuals available for SPC, but this book differs in two ways: (1) the basic tools of SPC are introduced in a no-nonsense, simple, non-math manner, and (2) the methods can be learned and practiced in an uncomplicated fashion using free software (eZ SPC 2.0), which is available to all readers online as a downloadable product. The book explains QC7 Tools, control charts, and statistical analysis including basic design of experiments. Theoretical explanations of the analytical methods are avoided; instead, results are interpreted through the use of the software.

Author : James Evans
Publisher : Pearson Education
Page : 231 pages
File Size : 38,73 MB
Release : 1991-03-29
Category : Technology & Engineering
ISBN : 0132442019

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With today's growing emphasis on quality improvement, training individuals in fundamental quality control skills is a major challenge. Professionals in manufacturing industries need to bring processes into statistical control – and maintain them. This book is designed to help readers learn the statistical tools and concepts needed to develop and use quality control effectively.