Statistics in Engineering: With Examples in MATLAB and R, Second Edition

Practical Statistical Thinking for Engineering Problems 📊

Engineering rarely unfolds in a world of perfect certainty. Measurements arrive with noise, processes drift, and design decisions require balancing evidence against risk. Statistics in Engineering brings the language of probability, estimation, and inference into that reality, with a dual focus on sound statistical reasoning and reproducible computational practice in MATLAB and R.

Rather than treating statistics as an abstract set of formulas, this second edition anchors each topic in engineering contexts. Readers work through examples where the analytical approach matters as much as the final number.

What the Book Covers

The text moves from fundamental ideas to practical inference:

• Probability and decision-making: axioms, conditional probability, Bayes’ theorem, and how uncertainty informs engineering choices.
• Graphical and descriptive statistics: visualizing data, summarizing distributions, and identifying outliers or unusual patterns.
• Discrete and continuous probability distributions: binomial, Poisson, normal, exponential, gamma, Gumbel, and related models commonly used in engineering.
• Correlation and functions of random variables: understanding relationships between measurements and propagating uncertainty through calculations.
• Estimation and inference: confidence intervals, hypothesis testing, comparing means and variances, and working with proportions.

Two Computing Languages, One Statistical Core 💻

A distinctive feature of this book is its paired treatment of MATLAB and R. Rather than forcing readers to choose a single tool, the examples show how each environment handles the same statistical task. This side-by-side approach helps engineers transfer skills between platforms and select the tool most convenient for a given problem.

Who Will Find It Useful

The material is designed for engineering students, practicing engineers, and technical professionals who want a mathematically grounded but application-oriented introduction to statistics. Readers with some exposure to calculus and linear algebra will be comfortable with the derivations, while the computational examples keep the focus on practical use.

Why the Second Edition Matters

As a second edition in the Chapman & Hall/CRC Texts in Statistical Science Series, this volume continues the approach of the original while offering a comprehensive introduction to engineering statistics. The emphasis on real engineering data makes it a useful reference long after the first read.

If you are looking for a statistics book that respects the practical demands of engineering work, this title offers a balanced path from core probability to confident data-driven decision making.