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| Peter Goos, David Meintrup | ||||
| Wiley | ||||
| 2015 | ||||
| English | ||||
| 368 pages | ||||
| 7.92 MB | ||||
[tab] [content title="Summary"] **Peter Goos**, Department of Statistics, University of Leuven, Faculty of Bio-Science Engineering, and **David Meintrup**, Department of Mathematics and Statistics, University of Applied Sciences Ingolstadt, Faculty of Mechanical Engineering, Germany **JMP: Graphs, Descriptive Statistics and Probability** offers a comprehensive introduction to foundational statistics and probability theory, enriched with numerous examples and applications utilizing JMP software. This book delivers a clear and thorough overview of key descriptive statistics relevant to nominal, ordinal, and quantitative data, with a special focus on graphical representations. The authors distinguish their work from many contemporary textbooks by blending theoretical and mathematical rigor with straightforward explanations of concepts. Throughout the text, JMP is employed for calculations, probability computations, and figure creation, ensuring that each example is elucidated with detailed instructions and screenshots. This approach fosters a solid understanding of both statistical theory and its practical applications. The book includes traditional visualizations like needle charts, histograms, and pie charts, alongside modern graphics such as mosaic plots, bubble plots, and heat maps. It also covers essential topics in probability theory, focusing on discrete probability distributions and continuous probability densities, including the binomial and Poisson distributions, as well as exponential, normal, and lognormal densities. A variety of examples are provided to illustrate these distributions and densities. **Key Features:** - Each concept is introduced with practical examples and demonstrations using JMP. - In-depth statistical theory is presented, complete with detailed mathematical derivations. - Each chapter features illustrative examples accompanied by step-by-step instructions and screenshots to enhance comprehension of statistical theory and its applications. - A supporting website provides datasets and additional teaching resources. This book is designed for students in engineering, economics, and natural sciences taking statistics courses, as well as advanced students in applied statistics and probability theory. It serves as a valuable resource for educators in applied statistics, offering a wealth of course material, examples, and practical applications. [/content] [content title="Content"] [/content] [content title="Author(s)"] [/content] [/tab]
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