Miller & Freund's Probability and Statistics for Engineers (Classic Version), 9th edition

For introductory, 1- or 2-semester, or sophomore/junior level courses in Probability and Statistics or Applied Statistics for engineering, physical science, and mathematics students.

A modern classic

Miller & Freund's Probability and Statistics for Engineers is rich in exercises and examples, and explores both elementary probability and basic statistics, with an emphasis on engineering and science applications. Much of the data has been collected from the author's own consulting experience and from discussions with scientists and engineers about the use of statistics in their fields. In later chapters, the text emphasizes designed experiments, especially 2-level factorial design. The 9th Edition includes several new datasets and examples showing application of statistics in scientific investigations, familiarizing students with the latest methods, and readying them to become real-world engineers and scientists.

This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price.

Hallmark features of this title

• A clear, concise presentation helps students quickly gain an understanding of the concepts.
• Rich problem sets give students the practice they need to learn the material.
• Do's and Don'ts at the end of each chapter help students to apply statistics correctly to avoid misuses.
• Computer exercises for MINITAB^® help students learn and become familiar with this software.
• Many data sets are drawn from the author's own consulting activities as well as discussions with scientists and engineers about their statistical problems.
• Content highlights include case studies in the first 2 chapters; graphs of the sampling distribution; summary tables of testing procedures; solid treatment of confidence interval techniques and hypothesis testing procedures; clear, current coverage of 2-level factorial design; a full chapter on modern ideas of quality improvement; accessible discussion on joint distributioins and the properties of expectation; and more.

New and updated features of this title

• Many new examples on important current engineering and scientific data further strengthen the text's orientation towards an applications-based introduction to statistics.
• Added graphs illustrating P-values appear in several examples along with an interpretation.
• More details about using R commands make it easy for students to check calculations on their own laptop or tablet, while reading an example.
• Key formulas are stressed and calculation formulas are downplayed. Computation formulas are set in the context of an application which only requires all, or mostly all, integer arithmetic, and now appear only at the end of sections. Students can then check their results with their choice of software.
• All examples are now numbered within each chapter.
• New data-based exercises feature real applications to help stimulate interest and strengthen a student's appreciation of the role of statistics in engineering applications.