Excel For Scientists And Engineers
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A Guide to Microsoft Excel 2013 for Scientists and Engineers
Completely updated guide for students, scientists and engineers who want to use Microsoft Excel 2013 to its full potential. Electronic spreadsheet analysis has become part of the everyday work of researchers in all areas of engineering and science. Microsoft Excel, as the industry standard spreadsheet, has a range of scientific functions that can be utilized for the modeling, analysis and presentation of quantitative data. This text provides a straightforward guide to using these functions of Microsoft Excel, guiding the reader from basic principles through to more complicated areas such as formulae, charts, curve-fitting, equation solving, integration, macros, statistical functions, and presenting quantitative data.
Excel for Scientists and Engineers
The Objective of This Book Numerical methods require extensive calculation, which is easily accomplished using today's desktop computers. A number of books have been written in which numerical methods are implemented using a specific programming language, such as FORTRAN or C++. Most scientists and engineers received some training in computer programming in their college days, but they (or their computer) may no longer have the capability to write or run programs in, for example, FORTRAN. This book shows how to implement numerical methods using Microsoft Excel@, the most widely used spreadsheet software package. Excel@ provides at least three ways for the scientist or engineer to apply numerical methods to problems: by implementing the methods on a worksheet, using worksheet formulas by using the built-in tools that are provided within Excel by writing programs, sometimes loosely referred to as macros, in Excel's Visual Basic for Applications (VBA) programming language. All of these approaches are illustrated in this book. This is a book about numerical methods. I have emphasized the methods and have kept the mathematical theory behind the methods to a minimum. In many cases, formulas are introduced with little or no description of the underlying theory. (I assume that the reader will be familiar with linear interpolation, simple calculus, regression, etc.) Other topics, such as cubic interpolation, methods for solving differential equations, and so on, are covered in more detail, and a few topics, such as Bairstow's method for obtaining the roots of a regular polynomial, are discussed in detail. In this book I have provided a wide range of Excel solutions to problems. In many cases I provide a series of examples that progress from a very simple implementation of the problem (useful for understanding the logic and construction of the spreadsheet or VBA code) to a more sophisticated one that is more general. Some of the VBA macros are simple "starting points" and I encourage the reader to modify them; others are (or at least I intended them to be) "finished products" that I hope users can employ on a regular basis. Nearly 100% of the material in this book applies equally to the PC or Macintosh versions of Excel. In a few cases I have pointed out the different keystrokes requires for the Macintosh version.
Statistics and Probability for Engineering Applications
Statistics and Probability for Engineering Applications provides a complete discussion of all the major topics typically covered in a college engineering statistics course. This textbook minimizes the derivations and mathematical theory, focusing instead on the information and techniques most needed and used in engineering applications. It is filled with practical techniques directly applicable on the job. Written by an experienced industry engineer and statistics professor, this book makes learning statistical methods easier for today's student. This book can be read sequentially like a normal textbook, but it is designed to be used as a handbook, pointing the reader to the topics and sections pertinent to a particular type of statistical problem. Each new concept is clearly and briefly described, whenever possible by relating it to previous topics. Then the student is given carefully chosen examples to deepen understanding of the basic ideas and how they are applied in engineering. The examples and case studies are taken from real-world engineering problems and use real data. A number of practice problems are provided for each section, with answers in the back for selected problems. This book will appeal to engineers in the entire engineering spectrum (electronics/electrical, mechanical, chemical, and civil engineering); engineering students and students taking computer science/computer engineering graduate courses; scientists needing to use applied statistical methods; and engineering technicians and technologists. * Filled with practical techniques directly applicable on the job* Contains hundreds of solved problems and case studies, using real data sets* Avoids unnecessary theory