Navidi W. Principles of Statistics for Engineers and Scientists

McGraw-Hill, 2010. — 594 p. — ISBN: 0077289315, 9780073376349.Principles of Statistics for Engineers and Scientists offers the same crystal clear presentation of applied statistics as Bill Navidi's Statistics for Engineers and Scientists text, in a manner especially designed for the needs of a one-semester course that focuses on applications.
The text features a unique approach accentuated by an engaging writing style that explains difficult concepts clearly. By presenting ideas in the context of real-world data featured in plentiful examples, the book motivates students to understand fundamental concepts through practical examples found in industry and research.Summarizing Univariate DataSampling
Summary Statistics
Graphical Summaries
Summarizing Bivariate DataThe Correlation Coefficient
The Least-Squares Line
Features and Limitations of the Least-Squares Line
ProbabilityBasic Ideas
Conditional Probability and Independence
Random Variables
Functions of Random Variables
Commonly Used DistributionsThe Binomial Distribution
The Poisson Distribution
The Normal Distribution
The Lognormal Distribution
The Exponential Distribution
Some Other Continuous Distributions
Probability Plots
The Central Limit Theorem
Point and Interval Estimation for a Single SamplePoint Estimation
Large-Sample Confidence Intervals for a Population Mean
Confidence Intervals for Proportions
Small-Sample Confidence Intervals for a Population Mean
Prediction Intervals and Tolerance Intervals
Hypothesis Tests for a Single SampleLarge-Saruple Tests for a Population Mean
Drawing Conclusions from the Results of Hypothesis Tests
Tests for a Population Proportion
Small-Sample Tests for a Population Mean
The Chi-Square Test
Fixed-Level Testing
Power
Multiple Tests
Inferences for Two SamplesLarge-Sample Inferences on the Difference Between Two Population Means
Inferences on the Difference Between Two Proportions
Small-Sample Inferences on the Difference Between Two Means
Inferences Using Paired Data
The F Test for Equality of Variance
Inference in Linear ModelsInferences Using the Least-Squares Coefficients
Checking Assumptions
Multiple Regression
Model Selection
Factorial ExperimentsOne-Factor Experiments
Pairwise Comparisons in One-Factor Experiments
Two-Factor Experiments
Randomized Complete Block Designs
2^P Factorial Experiments
Statistical Quality ControlBasic Ideas
Control Charts for Variables
Control Charts for Attributes
The CUSUM Chart
Process Capability
Appendix A: Tables
Appendix B: Bibliography
Answers to Selected Exercises