Essential Statistical Concepts for the Quality Professional


Book Description

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.




Practical Statistics for Data Scientists


Book Description

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




Statistical Concepts - A Second Course


Book Description

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.




The Art of Data Analysis


Book Description

A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: • Descriptive statistics • Analysis of variance • Probability and sample distributions • Confidence intervals • Hypothesis tests • Regression • Statistical correlation • Data collection • Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.




Basic Statistical Tools for Improving Quality


Book Description

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.




Practical Engineering, Process, and Reliability Statistics


Book Description

This book is a convenient and comprehensive guide to statistics. A resource for quality technicians and engineers in any industry, this second edition provides even more equations and examples for the reader—with a continued focus on algebra-based math. Those preparing for ASQ certification examinations, such as the Certified Quality Technician (CQT), Certified Six Sigma Green Belt (CSSGB), Certified Quality Engineer (CQE), Certified Six Sigma Black Belt (CSSBB), Certified Reliability Engineer (CRE), and Certified Supplier Quality Professional (CSQP), will find this book helpful as well. Inside you’ll ­find: • Complete calculations for determining confidence intervals, tolerances, sample size, outliers, process capability, and system reliability • Newly added equations for hypothesis tests (such as the Kruskal-Wallis test and Levene’s test for equality of variances), the Taguchi method, and Weibull and log-normal distributions • Hundreds of completed examples to demonstrate practical use of each equation • 20+ appendices, including distribution tables, critical values tables, control charts, sampling plans, and a beta table




Statistical Methods for Quality Improvement


Book Description

This text is highly recommended for managers and serious students of quality. Major US companies issue this reference and training manual to all managers during their quality training. This volume is also very valuable as a stand-alone reference on using statistics with a business and quality perspective.




A Review of Statistical Methods for Medical and Allied Health Professionals


Book Description

Statistics is a subject that benefits many other disciplines in its application and has contributed tremendously to the advancement of medicine. In recognition of the central role of statistics in the health fields, certification agencies have incorporated this science into their requirements for knowledge acquisition by their members. This recognition is also reflected in the board exams, particularly those taken for clinical board specialty certification tests. This book reinforces statistical principles for those who have taken a course in the subject during their years of education. It provides many examples and exercises to allow the reader to review the material discussed. Its concise presentation and the repetition of ideas throughout the text help solidify the reader’s learning and retention of knowledge of the various topics presented.







Promises to Keep


Book Description

Unlike Most Books On Quality Control, Which Contain Lot Of Theoretical Material And Statistics, This Book Has Been Written For The Production Managers, Shop-Floor Engineers And Supervisors, Who Actually Build Quality Into The Product. Modern Concepts And Techniques Of Total Quality Management Given In This Book Can Be Of Great Help In Meeting The Growing Challenge Of Competition, As Well As Increasing Productivity And Profitability.