Applied Statistics For Engineers

This concise book for engineering and sciences students emphasizes modern statistical methodology and data analysis. APPLIED STATISTICS FOR ENGINEERS AND SCIENTISTS is ideal for one-term courses that cover probability only to the extent that it is needed for inference. The authors emphasize application of methods to real problems, with real examples throughout. The text is designed to meet ABET standards and has been updated to reflect the most current methodology and practice. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Originally published in 1991. Textbook on the understanding and application of statistical procedures to engineering problems, for practicing engineers who once had an introductory course in statistics, but haven't used the techniques in a long time.

For courses in Probability and Statistics. This applied text for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important to students in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software (Microsoft Excel and Minitab) as well as in-depth coverage of quality and experimental design complete this treatment of statistics.

"Written by two of the leading figures in statistics, this highly regarded volume thoroughly addresses the full range of required topics." provides early discussed fundamental concepts such as variability, graphical representation of data, and randomization and blocking in design of experiments. provides a thorough introduction to descriptive statistics, including the importance of understanding variability, representation of data, exploratory data analysis, and time-sequence plots. explores principles of probability, probability distributions, and sampling distribution theory. discusses regression, design of experiments and their analysis, including factorial and fractional factorial designs.

* More Motivation - A completely revised chapter 1 gets students motivated right from the beginning. * Revised Probability Topics - The authors have revised and enhanced probability topics to promote even easier understanding. * Chapter Reorganization - Chapters on hypothesis testing and confidence intervals have been reorganized and rewritten. There is now expanded treatment of confidence intervals, prediction intervals, and tolerance intervals. * Real Engineering Applications - Treatment of all topics is oriented towards real engineering applications. In the probability chapters, the authors do not emphasize counting methods or artificial applications such as gambling. * Real Data, Real Engineering Situations - Examples and exercises throughout text use real data and real engineering situations. This motivates students to learn new concepts and gives them a taste of practical engineering experience. Use of the Computer - Computer usage is closely integrated into the text and homework exercises.

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Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with the tools.