Statistical Methods for Engineers
Brooks/Cole (Verlag)
978-0-495-01940-4 (ISBN)
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STATISTICAL METHODS FOR ENGINEERS by Geoff Vining and Scott Kowalski presents real engineering data and takes a truly modern approach to statistics. An engineering case study runs throughout the text and gives conceptual continuity through each chapter. An excellent opening introduces students to the connection and the intimate link between statistical decision making and engineering.
1. OVERTURE: ENGINEERING METHOD AND DATA COLLECTION. Need for Statistical Methods in Engineering. Engineering Method and Statistical Thinking. Statistical Thinking and Structured Problem Solving. Models. Obtaining Data. Sampling. Basic Principles of Experimental Design. Examples of Engineering Experiments. Purpose of Engineering Statistics. Case Study: Manufacture of Writing Instruments. Ideas for Projects. References. 2. DATA DISPLAYS. Importance of Data Displays. Stem-and-Leaf Displays. Boxplots. Using Computer Software. Using Boxplots to Analyze Designed Experiments. Case Study. Need for Probability and Distributions. Ideas for Projects. References. 3. MODELING RANDOM BEHAVIOR. Probability. 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. Case Study. References. 4. ESTIMATION AND TESTING. Estimation. Hypothesis Testing. Inference for a Single Mean. Inference for Proportions. Inference for Two Independent Samples. The Paired t-Test. Inference for Variances. Transformations and Nonparametric Analyses. Case Study. Ideas for Projects. References. 5. CONTROL CHARTS. Overview. Specifications Limits and Capability. X and R Charts. X and s-squared Charts. X-Chart. The NP-Chart. The C-Chart. Average Run Lengths. Standard Control Charts with Runs Rules. CUSUM and EWMA Charts. Case Study. Ideas for Projects. References. 6. LINEAR REGRESSION ANALYSIS. Relationships among Data. Simple Linear Regression. Multiple Linear Regression. Residual Analysis. Collinearity Diagnostics. Case Study. Ideas for Projects. References. 7. INTRODUCTION TO 2-to the k power FACTORIAL BASED EXPERIMENTS. The 2-squared Factorial Design. The 2-to-the-k power Factorial Design. Fractions of the 2-to-the-k power Factorial. Case Study. Ideas for Projects. References. 8. INTRODUCTION TO RESPONSES SURFACE METHODOLOGY. Sequential Philosophy of Experimentation. Central Composite Designs. Multiple Responses. Experimental Designs for Quality Improvement. Case Study. Ideas for Projects. 9. CODA. The Themes of This Course. Integrating the Themes. Statistics for Engineering. Appendix. Tables. Answers to Selected Exercises. Index.
| Erscheint lt. Verlag | 7.8.2005 |
|---|---|
| Verlagsort | CA |
| Sprache | englisch |
| Maße | 201 x 229 mm |
| Gewicht | 976 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Statistik |
| Technik | |
| ISBN-10 | 0-495-01940-2 / 0495019402 |
| ISBN-13 | 978-0-495-01940-4 / 9780495019404 |
| Zustand | Neuware |
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