eBook[PDF]

ISE Engineering Computation An Introduction Using MATLAB and Excel 2026 Release By Joseph Musto, William E. Howard

$30.00
Secure checkout
Instant digital download
PDF document

Document details

Pages
337
File size
9.68 MB
Format
Digital PDF
Category
eBook[PDF]
About this ebook
Engineering Computation: An Introduction Using MATLAB and Excel (2026 Release) by Joseph Musto and William E. Howard is a foundational textbook published by McGraw Hill. It is specifically designed to introduce first- and second-year engineering students to technical computing, algorithm development, and basic programming logic. [1, 2, 3]
The book is available through major academic and retail platforms, including the McGraw Hill Higher Education Catalog and Amazon. [1, 2, 3, 4, 5]
Core Focus and Approach
Rather than just teaching the mechanics of the software, the text prioritizes language-independent computational fundamentals. It highlights how to build algorithms, select the right tool for a problem, document engineering solutions, and verify outputs. It balances two primary tools: [1, 2, 3, 4, 5]
  • MATLAB: Used to teach structured programming logic (loops, condition statements, array structures) and high-level technical mathematics. [1]
  • Excel: Used as a ubiquitous, spreadsheet-driven environment for quick calculations, data tracking, and business-focused engineering tasks. [1, 2, 3, 4]
Book Structure and Chapters
The curriculum is divided into two distinct parts: [1, 2]
Part 1: Computational Tools [1]
  • Chapter 1: Computing Tools
  • Chapter 2: Excel Fundamentals
  • Chapter 3: MATLAB Fundamentals
  • Chapter 4: MATLAB Programming
  • Chapter 5: Plotting Data [1]
Part 2: Engineering Applications [1]
  • Covers essential numerical methods, including root-finding, matrix mathematics, systems of equations, integration, and optimization. [1]
Key Features
  • Step-by-Step Tutorials: Provides detailed, keystroke-level instructions for navigating MATLAB and Excel.
  • Comparative Approach: Guides students on choosing the appropriate tool for specific tasks.
  • Contextualized Learning: Integrates application-driven, real-world engineering problems. [1, 2, 3, 4, 5]

File included

PDF
tmpphpmdqccT 9.68 MB

Topics