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The book is intended for supply chain professionals, as well as for graduate and advanced undergraduate students. Practitioners will obtain valuable new insights and examples of implementable frameworks and methods for managing their supply chain functions and organizations. Students will develop an understanding of real-world approaches for supply chain planning, decision support, and many other key activities.

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The book is intended for supply chain professionals, as well as for graduate and advanced undergraduate students. Practitioners will obtain valuable new insights and examples of implementable frameworks and methods for managing their supply chain functions and organizations. Students will develop an understanding of real-world approaches for supply chain planning, decision support, and many other key activities.

Business --- Data mining. --- Decision making --- R (Computer program language) --- Data processing. --- Computer programs.

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The focus of this book is on data visualization and information visualization tools--two major categories of data visualization. The first part discusses the concepts and applications related to data analysis, visualization, and the current trend in data visualization. A discussion of systems and processes is provided as all data are collected from systems and processes. A section emphasizes the importance of variation in data analysis since almost all data show variation and the visual tools are an excellent way to study, analyze, and reduce the variation in the processes. Applications illustrate how the visual tools are an excellent means of viewing the current state of the process and provide the opportunities for improvement. The second part of the book is devoted to quality tools, a set of graphical and information visualization tools in data analysis, decision making, and Lean Six Sigma quality programs. The key application areas of visual tools including the business process improvement, business data analysis, health care, finance, manufacturing engineering, process improvement, and product and process design are discussed. The two categories of visualization tools--seven basic tools and seven new tools of quality-- are discussed with their applications. The basic quality tools are Process Maps, Check Sheets, Histograms, Scatter Diagrams, Run Charts, Control Charts, Cause-and-Effect (Ishikawa) Diagrams, and Pareto Charts/ Analysis. The seven new tools of quality--a set of visuals used to solve quality problems using graphical and analytical techniques--include the Affinity Diagram, Interrelationship Digraph, Tree Diagram, Prioritizing Matrices, Matrix Diagram, Process Decision Program Chart, and Activity Network Diagram. Other information processing tools, such as QFD-- the quality function deployment/house of quality--and multivari charts, are discussed using commonly used software.

Information visualization. --- Big data.

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This book creates a balance between the theory, practical applications, and computer implementation behind Regression--one of the most widely used techniques in analyzing and solving real world problems. The book begins with a thorough explanation of prerequisite knowledge with a discussion of Simple Regression Analysis including the computer applications. This is followed by Multiple Regression--a widely used tool to predict a response variable using two or more predictors. Since the analyses of regression models involve tedious and complex computations, complete computer analysis including the interpretation of multiple regression problems along with the model adequacy tests and residual analysis using widely used computer software are presented. The use of computers relieves the analyst of tedious, repetitive calculations, and allows one to focus on creating and interpreting successful models. Finally, the book extends the concepts to Regression and Modeling. Different models that provide a good fit to a set of data and provide a good prediction of the response variable are discussed. Among models discussed are the nonlinear, higher order, and interaction models, including models with qualitative variables. Computer analysis and interpretation of computer results are presented with real world applications. We also discuss all subset regression and stepwise regression with applications. Several flow charts are presented to illustrate the concepts. The statistical concepts for regression, computer instructions for the software-- Excel and MINITAB--used in the book and all of the data files used can be downloaded from the website link provided.

Regression analysis --- Data processing. --- coefficient of correlation --- correlation --- dependent variable --- dummy variable --- independent variable --- interaction model --- least squares estimates --- least squares prediction equation --- linear regression --- multiple coefficient of determination --- multiple regression and modeling --- nonlinear models --- regression line --- residual analysis --- scatterplot --- second-order model --- stepwise regression