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Statistical Methods For Engineers,9780538735186
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Statistical Methods For Engineers



Pub. Date:
Duxbury Press
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STATISTICAL METHODS FOR ENGINEERS offers a balanced, streamlined one-semester introduction to Engineering Statistics that emphasizes the statistical tools most needed by practicing engineers. Using real engineering problems with real data based on actual journals and consulting experience in the field, users see how statistics fits within the methods of engineering problem solving. The book teaches users how to think like an engineer at analyzing real data and planning a project the same way they will in their careers.

Table of Contents

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
Table of Contents provided by Publisher. All Rights Reserved.

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