This text presents numerical analysis in an easy and lucid manner requiring no prior knowledge of computer programming or intricacies of mathematics using MS-EXCEL 2000 through built in functions of MS-Excel depicting with ease various analysis. The analysis used can also be done using earlier versions of MS-Excel. The majority of numerical analysis needs fall into the curve fitting, interpolation, solutions of equations, integration methods. For these Excel's features provide a very easy and inexpensive way to get the job done.

This text is written primarily for students/readers who have a good background of high-school algebra, geometry, trigonometry, and the fundamentals of differential and integral calculus.

Learn to fully harness the power of Microsoft Excel® to perform scientific and engineering calculations With this text as your guide, you can significantly enhance Microsoft Excel's® capabilities to execute the calculations needed to solve a variety of chemical, biochemical, physical, engineering, biological, and medicinal problems. The text begins with two chapters that introduce you to Excel's Visual Basic for Applications (VBA) programming language, which allows you to expand Excel's® capabilities, although you can still use the text without learning VBA. Following the author's step-by-step instructions, here are just a few of the calculations you learn to perform: Use worksheet functions to work with matrices Find roots of equations and solve systems of simultaneous equations Solve ordinary differential equations and partial differential equations Perform linear and non-linear regression Use random numbers and the Monte Carlo method This text is loaded with examples ranging from very basic to highly sophisticated solutions. More than 100 end-of-chapter problems help you test and put your knowledge to practice solving real-world problems. Answers and explanatory notes for most of the problems are provided in an appendix. The CD-ROM that accompanies this text provides several useful features: All the spreadsheets, charts, and VBA code needed to perform the examples from the text Solutions to most of the end-of-chapter problems An add-in workbook with more than twenty custom functions This text does not require any background in programming, so it is suitable for both undergraduate and graduate courses. Moreover, practitioners in science and engineering will find that this guide saves hours of time by enabling them to perform most of their calculations with one familiar spreadsheet package

Annotation This text provides complete, clear, and detailed explanations of the principal numerical analysis methods and well known functions used in science and engineering. These are illustrated with many practical examples. With this text the reader learns numerical analysis with many real-world applications, MATLAB, and spreadsheets simultaneously. This text includes the following chapters:? Introduction to MATLAB? Root Approximations? Sinusoids and Complex Numbers? Matrices and Determinants? Review of Differential Equations? Fourier, Taylor, and Maclaurin Series? Finite Differences and Interpolation? Linear and Parabolic Regression? Solution of Differential Equations by Numerical Methods? Integration by Numerical Methods? Difference Equations? Partial Fraction Expansion? The Gamma and Beta Functions? Orthogonal Functions and Matrix Factorizations? Bessel, Legendre, and Chebyshev Polynomials? Optimization MethodsEach chapter contains numerous practical applications supplemented with detailed instructionsfor using MATLAB and/or Microsoft Excel? to obtain quick solutions.

The second edition of this book builds all the code example within a single project by incorporating new advancements in C# .NET technology and open-source math libraries. It also uses C# Interactive Window to test numerical computations without compiling or running the complete project code. The second edition includes three new chapters, including "Plotting", Fourier Analysis" and "Math Expression Parser". As in the first edition, this book presents an in-depth exposition of the various numerical methods used in real-world scientific and engineering computations. It emphasizes the practical aspects of C# numerical methods and mathematical functions programming, and discusses various techniques in details to enable you to implement these numerical methods in your .NET application. Ideal for scientists, engineers, and students who would like to become more adept at numerical methods, the second edition of this book covers the following content: - Overview of C# programming. - The mathematical background and fundamentals of numerical methods. - plotting the computation results using a 3D chart control. - Math libraries for complex numbers and functions, real and complex vector and matrix operations, and special functions. - Numerical methods for generating random numbers and random distribution functions. - Various numerical methods for solving linear and nonlinear equations. - Numerical differentiation and integration. - Interpolations and curve fitting. - Optimization of single-variable and multi-variable functions with a variety of techniques, including advanced simulated annealing and evolutionary algorithms. - Numerical techniques for solving ordinary differential equations. - Numerical methods for solving boundary value problems. - Eigenvalue problems. - Fourier analysis. - mathematical expression parser and evaluator. In addition, this book provides testing examples for every math function and numerical method to show you how to use these functions and methods in your own .NET applications in a manageable and step-by-step fashion. Please visit the author's website for more information about this book at https://drxudotnet.com https://drxudotnet.com and https://gincker.com.

This book is a printed edition of the Special Issue "Turbulence: Numerical Analysis, Modelling and Simulation" that was published in Fluids

The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes. The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications. Finally Chapter 5 comprises a collection of several methods for model-free data analyses.* Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes.* Provides examples of routines that are easily adapted to the processes investigated by the reader* 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered