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    Statistical Methods for Engineers

    ISBN-10: 053873518X
    ISBN-13: 9780538735186
    Edition: 3rd 2011
    List price: $341.95
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    List Price: $341.95
    Edition: 3rd
    Copyright Year: 2011
    Publisher: Brooks/Cole
    Publication Date: 1/1/2010
    Binding: Hardcover
    Pages: 648
    Size: 8.25" wide x 10.25" long x 1.00" tall
    Weight: 3.036
    Language: English

    Dr. Scott Kowalski received his Ph.D. from the University of Florida, Gainesville. He works as a Technical Trainer at Minitab, Inc. where he mentors Minitab's International Partners on their training efforts and teaches statistics to corporations in the United States, Asia and Australia. Prior to joining Minitab he taught at Stetson University and University of Central Florida. Dr. Kowalski is a Senior Member of ASQ, a member of the American Statistical Association, an Associate Editor for Quality Technology and Quantitative Management, and serves on the Editorial Review Board for the Journal of Quality Technology and Quality Engineering. Along with co-author Geoffrey Vining he was awarded the 2005 Nelson Award winner for paper with the "greatest immediate impact to practitioners" by the Journal of Quality Technology.

    Engineering Method and Data Collection
    Need for Statistical Methods in Engineering
    Engineering Method and Statistical Thinking
    Statistical Thinking and Structured Problem Solving
    Obtaining Data
    Basic Principles of Experimental Design
    Examples of Engineering Experiments
    Purpose of Engineering Statistics
    Case Study: Manufacture of Writing Instruments
    Ideas for Projects References
    Data Displays
    Importance of Data Displays
    Stem-and-Leaf Displays
    Using Computer Software
    Using Boxplots to Analyze Designed Experiments
    Case Study
    Need for Probability and Distributions
    Ideas for Projects References
    Modeling Random Behavior
    Random Variables and Distributions
    Discrete Random Variables
    Continuous Random Variables
    The Normal Distribution
    Random Behavior of Means
    Random Behavior of Means When the Variance Is Unknown
    Normal Approximation to the Binomial
    The Weibull Distribution for Reliability Applications
    Case Study References
    Estimation and Testing
    Hypothesis Testing
    Inference for a Single Mean
    Inference for a Single Proportion
    Inference for Two Independent Samples
    The Paired t-Test Inference for Two Proportions
    Inference for Variances
    Transformations and Nonparametric Analyses
    Case Study
    Ideas for Projects References
    Control Charts and Statistical Process Control
    Specification Limits
    X- and R-Charts
    X- and s?-Charts
    X-Chart. np-Chart. c-Chart
    Average Run Lengths
    Standard Control Charts with Runs Rules
    CUSUM and EWMA Charts
    Basic Process Capability Indices
    The SPC Approach to Gage R Studies
    Case Study
    Ideas for Projects References
    Linear Regression Analysis
    Relationships Among Data
    Simple Linear Regression
    Multiple Linear Regression
    Residual Analysis
    Collinearity Diagnostics
    Case Study
    Ideas for Projects References
    Introduction to 2k Factorial-Based Experiments
    The 2? Factorial Design
    The 2k Factorial Design
    Fractions of the 2k Factorial Design
    Case Study
    Ideas for Projects References
    Introduction to Response Surface Methodology
    Sequential Philosophy of Experimentation
    Central Composite Designs
    Box-Behnken Designs
    Multiple Responses
    Experimental Designs for Quality Improvement
    Case Study
    Ideas for Projects References
    The Themes of This Course
    Integrating the Themes
    Statistics and Engineering

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