Title: Experimentation: An Introduction to Measurement Theory and Experiment Design by D. C. Baird.

Format: Vintage 1960s English-language illustrated hardcover physics and measurement-theory textbook with dust jacket, produced in the United States by Prentice-Hall for young adult and adult readers in science and engineering.

Content overview: Introduces the nature of physical measurement and uncertainty and provides an elementary yet rigorous treatment of experiment design, emphasizing how to plan, carry out, and interpret laboratory work in physics and related disciplines.

Organization and themes: Develops topics such as the nature of measurement, statistical distributions of results, propagation of uncertainty in sums and differences of variables, processing of observations, and experiment evaluation, with appendices that supply more detailed mathematical justifications for results used in the main text.

Illustration and design: Text pages feature clear headings and numbered subsections, mathematical equations set in display format, worked examples, and occasional graphs and distribution curves that visualize error analysis and data interpretation, supported by explanatory jacket-flap notes highlighting the book's outstanding features.

Physical details: Medium-format clothbound hardcover with a black typographic dust jacket printed in cream and red lettering for the title and subtitle, and interior pages set in a readable serif type on off-white paper suitable for formulas and diagrams.

Publication details: Published by Prentice-Hall, Inc., Englewood Cliffs, New Jersey, and printed in the U.S. of America, reflecting the publisher's classic 1960s physics and engineering list.

Identifiers and audience: Nonfiction physics, measurement theory, and experimental design volume by D. C. Baird, Ph.D., Associate Professor of Physics at the Royal Military College of Canada, intended for university physics and engineering students, laboratory instructors, and readers interested in the principles of scientific experimentation and uncertainty analysis.