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Statistics With Jmp

Author: Peter Goos
Publisher: John Wiley & Sons
ISBN: 1119035759
Size: 22.21 MB
Format: PDF, ePub
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Peter Goos, Department of Statistics, University of Leuven, Faculty of Bio-Science Engineering and University of Antwerp, Faculty of Applied Economics, Belgium David Meintrup, Department of Mathematics and Statistics, University of Applied Sciences Ingolstadt, Faculty of Mechanical Engineering, Germany Thorough presentation of introductory statistics and probability theory, with numerous examples and applications using JMP JMP: Graphs, Descriptive Statistics and Probability provides an accessible and thorough overview of the most important descriptive statistics for nominal, ordinal and quantitative data with particular attention to graphical representations. The authors distinguish their approach from many modern textbooks on descriptive statistics and probability theory by offering a combination of theoretical and mathematical depth, and clear and detailed explanations of concepts. Throughout the book, the user-friendly, interactive statistical software package JMP is used for calculations, the computation of probabilities and the creation of figures. The examples are explained in detail, and accompanied by step-by-step instructions and screenshots. The reader will therefore develop an understanding of both the statistical theory and its applications. Traditional graphs such as needle charts, histograms and pie charts are included, as well as the more modern mosaic plots, bubble plots and heat maps. The authors discuss probability theory, particularly discrete probability distributions and continuous probability densities, including the binomial and Poisson distributions, and the exponential, normal and lognormal densities. They use numerous examples throughout to illustrate these distributions and densities. Key features: Introduces each concept with practical examples and demonstrations in JMP. Provides the statistical theory including detailed mathematical derivations. Presents illustrative examples in each chapter accompanied by step-by-step instructions and screenshots to help develop the reader’s understanding of both the statistical theory and its applications. A supporting website with data sets and other teaching materials. This book is equally aimed at students in engineering, economics and natural sciences who take classes in statistics as well as at masters/advanced students in applied statistics and probability theory. For teachers of applied statistics, this book provides a rich resource of course material, examples and applications.

Statistics With Jmp Hypothesis Tests Anova And Regression

Author: Peter Goos
Publisher: John Wiley & Sons
ISBN: 1119097045
Size: 40.35 MB
Format: PDF, Kindle
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Statistics with JMP: Hypothesis Tests, ANOVA and Regression Peter Goos, University of Leuven and University of Antwerp, Belgium David Meintrup, University of Applied Sciences Ingolstadt, Germany A first course on basic statistical methodology using JMP This book provides a first course on parameter estimation (point estimates and confidence interval estimates), hypothesis testing, ANOVA and simple linear regression. The authors approach combines mathematical depth with numerous examples and demonstrations using the JMP software. Key features: Provides a comprehensive and rigorous presentation of introductory statistics that has been extensively classroom tested. Pays attention to the usual parametric hypothesis tests as well as to non-parametric tests (including the calculation of exact p-values). Discusses the power of various statistical tests, along with examples in JMP to enable in-sight into this difficult topic. Promotes the use of graphs and confidence intervals in addition to p-values. Course materials and tutorials for teaching are available on the book's companion website. Masters and advanced students in applied statistics, industrial engineering, business engineering, civil engineering and bio-science engineering will find this book beneficial. It also provides a useful resource for teachers of statistics particularly in the area of engineering.

Elementary Statistics Using Jmp

Author: Sandra D. Schlotzhauer
Publisher: SAS Institute
ISBN: 1599944286
Size: 40.54 MB
Format: PDF, Mobi
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Learn how to perform basic statistical analyses using the powerful JMP software. Elementary Statistics Using JMP bridges the gap between statistics texts and JMP documentation. Author Sandra Schlotzhauer opens with an explanation of the basics of JMP data tables, demonstrating how to use JMP for descriptive statistics and graphs. The author continues with a lucid discussion of fundamental statistical concepts, including normality and hypothesis testing. Using a step-by-step approach, she shows analyses for comparing two groups, comparing multiple groups, fitting regression equations, and exploring contingency tables. For each analysis, the author clearly explains assumptions, the statistical approach, the JMP steps and results, and how to make conclusions from the results. Statistical methods include: *histograms, box plots, descriptive statistics, stem-and-leaf plots *mosaic plots, bar charts, and treemaps *t-tests and Wilcoxon tests to compare two independent or paired groups *one-way ANOVA and Kruskal-Wallis tests, and selected multiple comparison techniques *Pearson and Spearman correlation coefficients *regression models for lines, curves, and multiple variables *residuals plots and lack-of-fit tests for regression *Chi-square tests, Fisher's Exact test, and measures of association for contingency tables. Understand how to interpret both the graphs and text reports, as well as how to customize JMP results to meet your needs. Packed with examples from a broad range of industries, this text is ideal for novice to intermediate JMP users. Prior statistical knowledge, JMP experience, or programming skills are not required.

Jmp Start Statistics

Author: John Sall
Publisher: SAS Institute
ISBN: 1629608769
Size: 12.58 MB
Format: PDF, ePub, Docs
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This book provides hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP. Each chapter features concept-specific tutorials, examples, brief reviews of concepts, step-by-step illustrations, and exercises. Updated for JMP 13, JMP Start Statistics, Sixth Edition includes many new features, including: The redesigned Formula Editor. New and improved ways to create formulas in JMP directly from the data table or dialogs. Interface updates, including improved menu layout. Updates and enhancements in many analysis platforms. New ways to get data into JMP and to save and share JMP results. Many new features that make it easier to use JMP.

Biostatistics Using Jmp

Author: Trevor Bihl
Publisher: SAS Institute
ISBN: 1635262410
Size: 17.66 MB
Format: PDF, ePub, Mobi
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Analyze your biostatistics data with JMP! Trevor Bihl's Biostatistics Using JMP: A Practical Guide provides a practical introduction on using JMP, the interactive statistical discovery software, to solve biostatistical problems. Providing extensive breadth, from summary statistics to neural networks, this essential volume offers a comprehensive, step-by-step guide to using JMP to handle your data. The first biostatistical book to focus on software, Biostatistics Using JMP discusses such topics as data visualization, data wrangling, data cleaning, histograms, box plots, Pareto plots, scatter plots, hypothesis tests, confidence intervals, analysis of variance, regression, curve fitting, clustering, classification, discriminant analysis, neural networks, decision trees, logistic regression, survival analysis, control charts, and metaanalysis. Written for university students, professors, those who perform biological/biomedical experiments, laboratory managers, and research scientists, Biostatistics Using JMP provides a practical approach to using JMP to solve your biostatistical problems.

Jmp Essentials

Author: Curt Hinrichs
Publisher: SAS Institute
ISBN: 1629592889
Size: 55.96 MB
Format: PDF, ePub, Docs
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Grasp essential steps in order to generate meaningful results quickly with JMP. JMP Essentials: An Illustrated Step-by-Step Guide for New Users, Second Edition is designed for the new or occasional JMP user who needs to generate meaningful graphs or results quickly. Drawing on their own experience working with these customers, the authors provide essential steps for what new users typically need to carry out with JMP. This newest edition has all new instructions and screen shots reflecting the latest release of JMP software. In addition, it has eight new detailed sections and 10 new subsections that include creating maps, filtering data, creating dashboards, and working with Excel data, all of which highlight new, useful and basic level enhancements to JMP. The format of the book is unique. It adopts a show-and-tell design with essential step-by-step instructions and corresponding screen illustrations, which help users quickly see how to generate the desired results. In most cases, each section completes a JMP task, which maximizes the book's utility as a reference. In addition, each chapter contains a family of features that are carefully crafted to first introduce you to basic features and then on to more advanced ones. JMP Essentials: An Illustrated Step-by-Step Guide for New Users, Second Edition is the quickest and most accessible reference book available. This is part of the SAS Press program.

Modern Industrial Statistics

Author: Ron S. Kenett
Publisher: John Wiley & Sons
ISBN: 1118763696
Size: 25.68 MB
Format: PDF
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Fully revised and updated, this book combines a theoretical background with examples and references to R, MINITAB and JMP, enabling practitioners to find state-of-the-art material on both foundation and implementation tools to support their work. Topics addressed include computer-intensive data analysis, acceptance sampling, univariate and multivariate statistical process control, design of experiments, quality by design, and reliability using classical and Bayesian methods. The book can be used for workshops or courses on acceptance sampling, statistical process control, design of experiments, and reliability. Graduate and post-graduate students in the areas of statistical quality and engineering, as well as industrial statisticians, researchers and practitioners in these fields will all benefit from the comprehensive combination of theoretical and practical information provided in this single volume. Modern Industrial Statistics: With applications in R, MINITAB and JMP: Combines a practical approach with theoretical foundations and computational support. Provides examples in R using a dedicated package called MISTAT, and also refers to MINITAB and JMP. Includes exercises at the end of each chapter to aid learning and test knowledge. Provides over 40 data sets representing real-life case studies. Is complemented by a comprehensive website providing an introduction to R, and installations of JMP scripts and MINITAB macros, including effective tutorials with introductory material: www.wiley.com/go/modern_industrial_statistics.

Jmp Means Business

Author: Josef Schmee
Publisher: SAS Institute
ISBN: 1607644274
Size: 39.98 MB
Format: PDF, Kindle
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Designed for business and MBA students, as well as industry professionals who need to use and interpret statistics, "JMP Means Business" covers data collection, descriptive statistics, distributions, confidence intervals and hypothesis tests, and more.

Practical Data Analysis With Jmp Second Edition

Author: Robert Carver
Publisher: SAS Institute
ISBN: 1629592641
Size: 16.51 MB
Format: PDF, ePub, Docs
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Understand the concepts and techniques of analysis while learning to reason statistically. Being an effective analyst requires that you know how to properly define a problem and apply suitable statistical techniques, as well as clearly and honestly communicate the results with information-rich visualizations and precise language. Being a well-informed consumer of analyses requires the same set of skills so that you can recognize credible, actionable research when you see it. Robert Carver's Practical Data Analysis with JMP, Second Edition uses the powerful interactive and visual approach of JMP to introduce readers to the logic and methods of statistical thinking and data analysis. It enables you to discriminate among and to use fundamental techniques of analysis, enabling you to engage in statistical thinking by analyzing real-world problems. “Application Scenarios” at the end of each chapter challenge you to put your knowledge and skills to use with data sets that go beyond mere repetition of chapter examples, and three new review chapters help readers integrate ideas and techniques. In addition, the scope and sequence of the chapters have been updated with more coverage of data management and analysis of data. The book can stand on its own as a learning resource for professionals or be used to supplement a standard college-level introduction-to-statistics textbook. It includes varied examples and problems that rely on real sets of data, typically starting with an important or interesting research question that an investigator has pursued. Reflective of the broad applicability of statistical reasoning, the problems come from a wide variety of disciplines, including engineering, life sciences, business, economics, among Practical Data Analysis with JMP, Second Edition introduces you to the major platforms and essential features of JMP and will leave you with a sufficient background and the confidence to continue your exploration independently. This book is part of the SAS Press program.

Optimal Design Of Experiments

Author: Peter Goos
Publisher: John Wiley & Sons
ISBN: 1119976162
Size: 24.95 MB
Format: PDF, Mobi
View: 3433
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"This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.