ISE Principles of Statistics for Engineers & Scientists

Höfundur: William Navidi (Útgáfa: 2)
ISE Principles of Statistics for Engineers & Scientists

Kaup valmöguleikar

Available for the first time in McGraw-Hill's Connect! Principles of Statistics for Engineers and Scientists emphasizes statistical methods and how they can be applied to problems in science and engineering. The book contains many examples that feature real, contemporary data sets, both to motivate students and to show connections to industry and scientific research. Because statistical analyses are done on computers, the book contains exercises and examples that involve interpreting, as well as generating, computer output.

Nánar um bókina

Útgefandi
McGraw-Hill Higher Education (International)
ISBN
9781260589474
Print ISBN
9781260570731
Format
ePub
Útgáfa
2
Höfundar
William Navidi
Tungumál
English
Útgefið
2020-01-07
Prent takmörkun á líftíma
100
Prent takmörkun
2
Afritunar takmörkun
2

Kaflar

  • Cover
  • Title Page
  • Copyright Page
  • Dedication
  • About the Author
  • Contents
  • Preface
  • Connect
  • Chapter 1 Summarizing Univariate Data
  • Introduction
  • 1.1 Sampling
  • 1.2 Summary Statistics
  • 1.3 Graphical Summaries
  • Chapter 2 Summarizing Bivariate Data
  • Introduction
  • 2.1 The Correlation Coefficient
  • 2.2 The Least-Squares Line
  • 2.3 Features and Limitations of the Least-Squares Line
  • Chapter 3 Probability
  • Introduction
  • 3.1 Basic Ideas
  • 3.2 Conditional Probability and Independence
  • 3.3 Random Variables
  • 3.4 Functions of Random Variables
  • Chapter 4 Commonly Used Distributions
  • Introduction
  • 4.1 The Binomial Distribution
  • 4.2 The Poisson Distribution
  • 4.3 The Normal Distribution
  • 4.4 The Lognormal Distribution
  • 4.5 The Exponential Distribution
  • 4.6 Some Other Continuous Distributions
  • 4.7 Probability Plots
  • 4.8 The Central Limit Theorem
  • Chapter 5 Point and Interval Estimation for
  • Introduction
  • 5.1 Point Estimation
  • 5.2 Large-Sample Confidence Intervals for a Population Mean
  • 5.3 Confidence Intervals for Proportions
  • 5.4 Small-Sample Confidence Intervals for a Population Mean
  • 5.5 Prediction Intervals and Tolerance Intervals
  • Chapter 6 Hypothesis Tests for a Single Sample
  • Introduction
  • 6.1 Large-Sample Tests for a Population Mean
  • 6.2 Drawing Conclusions from the Results of Hypothesis Tests
  • 6.3 Tests for a Population Proportion
  • 6.4 Small-Sample Tests for a Population Mean
  • 6.5 The Chi-Square Test
  • 6.6 Fixed-Level Testing
  • 6.7 Power
  • 6.8 Multiple Tests
  • Chapter 7 Inferences for Two Samples
  • Introduction
  • 7.1 Large-Sample Inferences on the Difference Between Two Population Means
  • 7.2 Inferences on the Difference Between Two Proportions
  • 7.3 Small-Sample Inferences on the Difference Between Two Means
  • 7.4 Inferences Using Paired Data
  • 7.5 Tests for Variances of Normal Populations
  • Chapter 8 Inference in Linear Models
  • Introduction
  • 8.1 Inferences Using the Least-Squares Coefficients
  • 8.2 Checking Assumptions
  • 8.3 Multiple Regression
  • 8.4 Model Selection
  • Chapter 9 Factorial Experiments
  • Introduction
  • 9.1 One-Factor Experiments
  • 9.2 Pairwise Comparisons in One-Factor Experiments
  • 9.3 Two-Factor Experiments
  • 9.4 Randomized Complete Block Designs
  • 9.5 2p Fractional Experiment
  • Chapter 10 Statistical Quality Control
  • Introduction
  • 10.1 Basic Ideas
  • 10.2 Control Charts for Variables
  • 10.3 Control Charts for Attributes
  • 10.4 The CUSUM Chart
  • 10.5 Process Capability
  • Appendix A: Tables
  • Appendix B: Bibliography
  • Answers to Selected Exercises
  • index