The text provides a practical approach oriented to engineering as well as chemical and physical sciences. Students learn how the material will be relevant in their careers through the integration throughout of unique problem sets that reflect realistic applications and situations. Applied Statistics, 5e is suitable for either a one- or two-term course in probability and statistics.

- Because computer-intensive methods are so important in the modern use of statistics, material on the bootstrap and its use in constructing confidence intervals has been added
- Increased emphasis on the use of P-value in hypothesis testing, throughout the text
- Explanations throughout the book have been refined to clarify the concepts, making them easier for students to understand.
- The introductory chapter on hypothesis testing now includes coverage of equivalence testing, a technique widely used in the biopharmaceutical industry, but which also has widespread applications in other areas.
- Combining P-values when performing multiple tests is included.
- Many new examples and almost entirely revised homework exercises sections.

1 The Role of Statistics in Engineering

2 Probability

3 Discrete Random Variables and Probability Distributions

4 Continuous Random Variables and Probability Distributions

5 Joint Probability Distributions

6 Descriptive Statistics

7 Sampling Distributions and Point Estimation of Parameters

8 Statistical Intervals for a Single Sample

9 Tests of Hypotheses for a Single Sample

10 Statistical Inference for Two Samples

11 Simple Linear Regression and Correlation

12 Multiple Linear Regression

13 Design and Analysis of Single-Factor Experiments: The Analysis of Variance

14 Design of Experiments with Several Factors

15 Statistical Quality Control

Appendices

2 Probability

3 Discrete Random Variables and Probability Distributions

4 Continuous Random Variables and Probability Distributions

5 Joint Probability Distributions

6 Descriptive Statistics

7 Sampling Distributions and Point Estimation of Parameters

8 Statistical Intervals for a Single Sample

9 Tests of Hypotheses for a Single Sample

10 Statistical Inference for Two Samples

11 Simple Linear Regression and Correlation

12 Multiple Linear Regression

13 Design and Analysis of Single-Factor Experiments: The Analysis of Variance

14 Design of Experiments with Several Factors

15 Statistical Quality Control

Appendices

REVIEW

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