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The author develops and illustrates statistical ideas in the context of the kinds of practical data analysis that managers actually undertake, starting with the simple applications to quality control. MINITAB is used throughout allowing students to perform meaningful statistical computations and to concentrate on learning how statistics can be used effectively in business. Written for introductory courses in business statistics (especially at MBA level), the new edition offers a simpler yet more systematic and thorough approach to data analysis and incorporates new features of MINITAB Release 7, especially control chart commands.
This guide has been written to support all those who gather, analyse, and interpret data in the course of their work. The guide aims to remove some of the mystique surrounding statistics as well as showing how the techniques can be used to arrive at decisions in a logical data driven manner. This guide should be of interest and use to Six Sigma Green and Black Belts, Operations Scientists and Managers, Social Science Students and Practitioners as well as those involved in practical statistical analysis for many other reasons. For each technique this guide explains what the technique is and how it is used, it shows how to enter the data into MINITAB 18®, provides logical click-by-click instructions on how to execute each technique and explains how to interpret the results. The data files and example worksheets may be downloaded to aid the user.
Explains statistical tests for Minitab using the same formulae-free, non-technical approach as the very successful SPSS version. Social science students will welcome this integrated, non-mathematical introduction.
Six Sigma statistical methodology using Minitab Problem Solving and Data Analysis using Minitab presents example-based learning to aid readers in understanding how to use MINITAB 16 for statistical analysis and problem solving. Each example and exercise is broken down into the exact steps that must be followed in order to take the reader through key learning points and work through complex analyses. Exercises are featured at the end of each example so that the reader can be assured that they have understood the key learning points. Key features: Provides readers with a step by step guide to problem solving and statistical analysis using Minitab 16 which is also compatible with version 15. Includes fully worked examples with graphics showing menu selections and Minitab outputs. Uses example based learning that the reader can work through at their pace. Contains hundreds of screenshots to aid the reader, along with explanations of the statistics being performed and interpretation of results. Presents the core statistical techniques used by Six Sigma Black Belts. Contains examples, exercises and solutions throughout, and is supported by an accompanying website featuring the numerous example data sets. Making Six Sigma statistical methodology accessible to beginners, this book is aimed at numerical professionals, students or academics who wish to learn and apply statistical techniques for problem solving, process improvement or data analysis whilst keeping mathematical theory to a minimum.
Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented. Industrial Statistics with MINITAB: Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry. Explores statistical techniques and how they can be used effectively with the help of MINITAB 16. Contains extensive illustrative examples and case studies throughout and assumes no previous statistical knowledge. Emphasises data graphics and visualization, and the most used industrial statistical tools, such as Statistical Process Control and Design of Experiments. Is supported by an accompanying website featuring case studies and the corresponding datasets. Six Sigma Green Belts and Black Belts will find explanations and examples of the most relevant techniques in DMAIC projects. The book can also be used as quick reference enabling the reader to be confident enough to explore other MINITAB capabilities.
Statistics can't be over simplified, but it can be clarified and made fun to learn. Abranovic was inspired by his own students' positive reactions to create a textbook that succeeds by encouraging self-study, presenting new concepts in bitesize chunks, and moving the learner enjoyably toward active statistical analysis. Statistical Thinking and Data Analysis Methods for Managers includes data sets on diskettes and employs up-to-date Exploratory Data Analysis (EDA) tools, such as stem-and-leaf diagrams and box plots, without Sacrificing traditional methods and intellectual rigor. Designed for introductory courses and adaptable to graduate study, the text diminishes the need for spending classroom time on computational formulas. With its strong approach and use of global examples throughout, it will appeal to those who want heavy problem use and international applications.
This manual is appropriate for any introductory statistics or business statistics course where Minitab is being used. Organized to correspond to the table of contents of most statistics texts. The guide provides step by step instruction in using Minitab sessions or windows' commands for statistical analysis. Based on Minitab Release 11.0.
Reflecting the latest trends and methodologies, this comprehensive and innovative study on business statistics uses a practical, data-analytic approach. Based on the development of a survey which integrates the various topics and provides a cohesive study of descriptive statistics, probability, statistical inference, and regression analysis, it now focuses on data analysis and interpretation of computer output with a reduced focus on hand calculations. Creates an Employee Satisfaction Survey yielding 400 sample responses which readers can use to integrate such topics as descriptive statistics, probability, statistical inference, and regression analysis. Offers over 1200 realistic applications problems, 170 Survey/Database Projects, and relevant case studies. Contains two distinct types of summary sections to facilitate understanding - Exploratory and Confirmatory Data Analysis sections (looking at the four components of good data analysis - plotting, observing, computing and describing), and Ethical Issue sections (helps readers learn to think critically about the ramifications of the ethical issues involved in data analysis). Provides thorough coverage of regression and multiple regression, and considers many popular methodologies, including exploratory data analysis (EDA) techniques and dot charts, Pareto diagrams and supertables. Now opens each chapter with a "Using Statistics" example that shows how statistics can be applied to accounting, finance, management or marketing - plus includes appendices on using Microsoft Excel 97 and Minitab; an additional chapter on multiple regression that focuses on model building; a new chapter on decision making; a running case study, and more.