
Liengme's Guide to Excel 2016 for Scientists and Engineers
(Windows and Mac)
Description
Key Features
- Content written specifically for the requirements of science and engineering students and professionals working with Microsoft Excel, brought fully up to date with Microsoft Office release of Excel 2016.
- Features of Excel 2016 are illustrated through a wide variety of examples based on technical contexts, demonstrating the use of the program for analysis and presentation of experimental results.
- Where appropriate, demonstrates the differences between the PC and Mac versions of Excel.
- Includes many new end-of-chapter problems at varying levels of difficulty.
Readership
Undergraduate science and engineering students; professional scientists and engineers
Table of Contents
- 1. Welcome to Microsoft Excel 2016
2. Basic Operations
3. Printing in Excel
4. Using Functions
5. Decision Functions
6. Data Mining
7. Charting
8. Regression Analysis
9. VBA User-Defined Functions
10. VBA Subroutines
11. Modeling I
12. Using Solver
13. Numerical Integration
14. Differential Equations
15. Modeling II
16. Statistics for Experimenters
Product details
- No. of pages: 414
- Language: English
- Copyright: © Academic Press 2019
- Published: August 14, 2019
- Imprint: Academic Press
- Paperback ISBN: 9780128182499
- eBook ISBN: 9780128182505
About the Authors
Bernard Liengme
Affiliations and Expertise
Keith Hekman
Affiliations and Expertise
Ratings and Reviews
Latest reviews
(Total rating for all reviews)
LesSkinner Fri Apr 03 2020
Liengme's Guide to Excel 2016
An excellent "how to" book using Excel 2016. Good examples and exercises in each subchapter. Starts with basics of Excel and goes through advanced features including the new ones added in this version of Excel. A good read and well worth the price.
Nicki D. Sun Mar 08 2020
Excellent primer showing the power of MS Excel
This is a really useful book, it is clearly laid out and sensibly structured. The authors do an excellent job of showing how useful MS Excel can be for much of the data analysis and modelling the engineers and scientist undertake.