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  • 1
    Language: English
    Pages: 1 online resource (xi, 912, A1-A23, [15], B1-B18, C1-C4, I1-I6 p.) , ill.
    Edition: Preliminary ed.
    Parallel Title: Erscheint auch als
    Keywords: Mathematical statistics ; Probabilities ; Experimental design ; Quality control ; Electronic books ; Electronic books ; local
    Abstract: All statistical concepts are supported by a large number of examples using data encountered in real life situations; and the text illustrates how the statistical packages MINITAB®, Microsoft Excel ®, and JMP® may be used to aid in the analysis of various data sets. The text also covers an appropriate and understandable level of the design of experiments. This includes randomized block designs, one and two-way designs, Latin square designs, factorial designs, response surface designs, and others. This text is suitable for a one- or two-semester calculus-based undergraduate statistics course for engineers and scientists, and the presentation of material gives instructors flexibility to pick and choose topics for their particular courses.
    Note: Includes bibliographical references (p. C1-C4) and index. - Description based on print version record
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  • 2
    ISBN: 9781119516637
    Language: English
    Pages: 1 online resource (1040 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Introduces basic concepts in probability and statistics to data science students, as well as engineers and scientists Aimed at undergraduate/graduate-level engineering and natural science students, this timely, fully updated edition of a popular book on statistics and probability shows how real-world problems can be solved using statistical concepts. It removes Excel exhibits and replaces them with R software throughout, and updates both MINITAB and JMP software instructions and content. A new chapter discussing data mining—including big data, classification, machine learning, and visualization—is featured. Another new chapter covers cluster analysis methodologies in hierarchical, nonhierarchical, and model based clustering. The book also offers a chapter on Response Surfaces that previously appeared on the book’s companion website. Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP, Second Edition is broken into two parts. Part I covers topics such as: describing data graphically and numerically, elements of probability, discrete and continuous random variables and their probability distributions, distribution functions of random variables, sampling distributions, estimation of population parameters and hypothesis testing. Part II covers: elements of reliability theory, data mining, cluster analysis, analysis of categorical data, nonparametric tests, simple and multiple linear regression analysis, analysis of variance, factorial designs, response surfaces, and statistical quality control (SQC) including phase I and phase II control charts. The appendices contain statistical tables and charts and answers to selected problems. Features two new chapters—one on Data Mining and another on Cluster Analysis Now contains R exhibits including code, graphical display, and some results MINITAB and JMP have been updated to their latest versions Emphasizes the p-value approach and includes related practical interpretations Offers a more applied statistical focus, and features modified examples to better exhibit statistical concepts Supplemented with an Instructor's-only solutions manual on a book’s companion website Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP is an excellent text for graduate level data science students, and engineers and scientists. It is also an ideal introduction to applied statistics and probability for undergraduate students in engi...
    Note: Online resource; Title from title page (viewed February 5, 2020) , Mode of access: World Wide Web.
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  • 3
    ISBN: 9781118501696 , 1118501691
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Parallel Title: Erscheint auch als
    Keywords: Probabilities ; Mathematical statistics ; Electronic books ; Electronic books ; local
    Abstract: Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab and Microsoft Office Excel to analyze various data sets. The book also features: Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.
    Note: Includes bibliographical references and index. - Description based on print version record
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