Applied Engineering Statistics Applied Engineering Statistics

Applied Engineering Statistics

    • ¥8,800
    • ¥8,800

Publisher Description

Thoroughly updated throughout, this second edition will continue to be about the practicable methods of statistical applications for engineers, and as well for scientists and those in business. It remains a what-I-wish-I-had-known-when-starting-my-career compilation of techniques.

Contrasting a mathematical and abstract orientation of many statistics texts, which expresses the science/math values of researchers, this book has its focus on the application to concrete examples and the interpretation of outcomes. Supporting application propriety, this book also presents the fundamental concepts, provides supporting derivation, and has frequent do and not-do notes.

Key Features:
Contains details of the computation for the examples. Includes new examples and exercises. Includes expanded topics supporting data analysis.
The book is for upper-level undergraduate or graduate students in engineering, the hard sciences, or business programs. The intent is that the text would continue to be useful in professional life, and appropriate as a self-learning tool after graduation – whether in graduate school or in professional practice.

Errata can be found here

GENRE
Science & Nature
RELEASED
2021
November 1
LANGUAGE
EN
English
LENGTH
500
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
13.4
MB
Statistics for Technology Statistics for Technology
2018
Nonlinear Regression Modeling for Engineering Applications Nonlinear Regression Modeling for Engineering Applications
2016
Data Driven Statistical Methods Data Driven Statistical Methods
2019
Evidence-Based Statistics Evidence-Based Statistics
2020
Introduction to Statistical Modelling and Inference Introduction to Statistical Modelling and Inference
2022
Introduction to Statistical Analysis of Laboratory Data Introduction to Statistical Analysis of Laboratory Data
2015
Engineering Optimization Engineering Optimization
2018
Nonlinear Regression Modeling for Engineering Applications Nonlinear Regression Modeling for Engineering Applications
2016