Engineering Statistics 5th Edition by John Wiley and Sons- Ebook PDF Instant Download/Delivery: 0470631473 978-0470631478
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ISBN 10: 0470631473
ISBN 13: 978-0470631478
Author: John Wiley and Sons
Montgomery, Runger, and Hubele’s Engineering Statistics, 5th Edition provides modern coverage of engineering statistics by focusing on how statistical tools are integrated into the engineering problem-solving process. All major aspects of engineering statistics are covered, including descriptive statistics, probability and probability distributions, statistical test and confidence intervals for one and two samples, building regression models, designing and analyzing engineering experiments, and statistical process control. This edition features new introductions, revised content to help students better understand ANOVA, new examples to help calculate probability and approximately 80 new exercises.
Engineering Statistics 5th Table of contents:
CHAPTER 1 The Role of Statistics in Engineering.
1-1 The Engineering Method and Statistical Thinking.
1-2 Collecting Engineering Data.
1-3 Mechanistic and Empirical Models.
1-4 Observing Processes Over Time.
CHAPTER 2 Data Summary and Presentation.
2-1 Data Summary and Display.
2-2 Stem-and-Leaf Diagram.
2-3 Histograms.
2-4 Box Plot.
2-5 Time Series Plots.
2-6 Multivariate Data.
CHAPTER 3 Random Variables and Probability Distributions.
3-1 Introduction.
3-2 Random Variables.
3-3 Probability.
3-4 Continuous Random Variables.
3-5 Important Continuous Distributions.
3-6 Probability Plots.
3-7 Discrete Random Variables.
3-8 Binomial Distribution.
3-9 Poisson Process.
3-10 Normal Approximation to the Binomial and Poisson Distributions.
3-11 More than One Random Variable and Independence.
3-12 Functions of Random Variables.
3-13 Random Samples, Statistics, and the Central Limit Theorem.
CHAPTER 4 Decision Making for a Single Sample.
4-1 Statistical Inference.
4-2 Point Estimation.
4-3 Hypothesis Testing.
4-4 Inference on the Mean of a Population, Variance Known.
4-5 Inference on the Mean of a Population, Variance Unknown.
4-6 Inference on the Variance of a Normal Population.
4-7 Inference on a Population Proportion.
4-8 Other Interval Estimates for a Single Sample.
4-9 Summary Tables of Inference Procedures for a Single Sample.
4-10 Testing for Goodness of Fit.
CHAPTER 5 Decision Making for Two Samples.
5-1 Introduction.
5-2 Inference on the Means of Two Populations, Variances Known.
5-3 Inference on the Means of Two Populations, Variances Unknown.
5-4 The Paired t-Test.
5-5 Inference on the Ratio of Variances of Two Normal Populations.
5-6 Inference on Two Population Proportions.
5-7 Summary Tables for Inference Procedures for Two Samples.
5-8 What if We Have More than Two Samples?
CHAPTER 6 Building Empirical Models.
6-1 Introduction to Empirical Models.
6-2 Simple Linear Regression.
6-3 Multiple Regression.
6-4 Other Aspects of Regression.
CHAPTER 7 Design of Engineering Experiments.
7-1 The Strategy of Experimentation.
7-2 Factorial Experiments.
7-3 2k Factorial Design.
7-4 Center Points and Blocking in 2k Designs.
7-5 Fractional Replication of a 2k Design.
7-6 Response Surface Methods and Designs.
7-7 Factorial Experiments With More Than Two Levels.
CHAPTER 8 Statistical Process Control.
8-1 Quality Improvement and Statistical Process Control.
8-2 Introduction to Control Charts.
8-3 X and R Control Charts.
8-4 Control Charts For Individual Measurements.
8-5 Process Capability.
8-6 Attribute Control Charts.
8-7 Control Chart Performance.
8-8 Measurement Systems Capability.
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