Name: Design of Experiments and Hypothesis Testing (en Inglés)
SKU: 66205316
Price: 79.68 USD
Availability: InStock
Author: Maurya, Nagendra Kumar; Mustafa, Jiyaul; Pandey, Abhishek

portada Design of Experiments and Hypothesis Testing (en Inglés)

Design of Experiments and Hypothesis Testing (en Inglés)

Formato

Libro Físico

Editorial

LAP Lambert Academic Publishing

Autor

Maurya, Nagendra Kumar; Mustafa, Jiyaul; Pandey, Abhishek

Idioma

Inglés

N° páginas

108

Encuadernación

Tapa Blanda

Dimensiones

22.9x15.2x0.7 cm

ISBN13

9786208425401

Design of Experiments and Hypothesis Testing (en Inglés)

Maurya, Nagendra Kumar; Mustafa, Jiyaul; Pandey, Abhishek (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

Libro Nuevo Importado

Envío: 26 a 33 días háb.

$ 144.87$ 79.68

-45%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan 10 unidades

$ 79.68

Llega entre el 23 Sep y el 06 Oct a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Design of Experiments and Hypothesis Testing (en Inglés)"

Design of Experiments and Hypothesis Testing: A Practical Approach for Engineers and Researchers offers a comprehensive, application-focused guide to planning, conducting, and analyzing experiments in engineering and scientific research. Structured into four parts, the book begins with the foundations of statistical thinking, covering experimental design principles, statistical inference, and data measurement scales. It then explores key DOE techniques, including full factorial designs, Response Surface Methodology (RSM), and Taguchi methods for robust design. The hypothesis testing section explains statistical errors, ANOVA, and non-parametric tests, equipping readers to make sound, data-driven decisions. The final section addresses multi-objective optimization, introducing Pareto fronts, trade-offs, and real-world engineering applications. This book bridges the gap between theory and practice, making complex statistical concepts accessible. It is an essential resource for students, researchers, and practicing engineers seeking to enhance process quality, optimize performance, and innovate through data-driven problem-solving.