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Author: Bernard V Liengme
Publisher: Morgan & Claypool Publishers
ISBN: 1627057056
Category : Science
Languages : en
Pages : 205
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Book Description
This book demonstrates some of the ways in which Microsoft Excel® may be used to solve numerical problems in the field of physics. But why use Excel in the first place? Certainly, Excel is never going to out-perform the wonderful symbolic algebra tools tha
Author: Bernard V Liengme
Publisher: Morgan & Claypool Publishers
ISBN: 1627057056
Category : Science
Languages : en
Pages : 205
Get Book Here
Book Description
This book demonstrates some of the ways in which Microsoft Excel® may be used to solve numerical problems in the field of physics. But why use Excel in the first place? Certainly, Excel is never going to out-perform the wonderful symbolic algebra tools tha
Author: Bernard V Liengme
Publisher: Morgan & Claypool Publishers
ISBN: 1627054197
Category : Science
Languages : en
Pages : 95
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Book Description
This book demonstrates some of the ways in which Microsoft Excel® may be used to solve numerical problems in the field of physics. But why use Excel in the first place? Certainly, Excel is never going to out-perform the wonderful symbolic algebra tools tha
Author: B Liengme
Publisher: Myprint
ISBN: 9781681748078
Category :
Languages : en
Pages : 96
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Book Description
Author: Shinil Cho
Publisher: Morgan & Claypool Publishers
ISBN: 164327726X
Category : Science
Languages : en
Pages : 162
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Book Description
This book covers essential Microsoft EXCEL®'s computational skills while analyzing introductory physics projects. Topics of numerical analysis include; multiple graphs on the same sheet, calculation of descriptive statistical parameters, a 3-point interpolation, the Euler and the Runge-Kutter methods to solve equations of motion, the Fourier transform to calculate the normal modes of a double pendulum, matrix calculations to solve coupled linear equations of a DC circuit, animation of waves and Lissajous figures, electric and magnetic field calculations from the Poisson equation and its 3D surface graphs, variational calculus such as Fermat's least traveling time principle and the least action principle. Nelson's stochastic quantum dynamics is also introduced to draw quantum particle trajectories.
Author: Bernard V Liengme
Publisher: Morgan & Claypool Publishers
ISBN: 1681744627
Category : Science
Languages : en
Pages : 99
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Book Description
This book is both an introduction and a demonstration of how Visual Basic for Applications (VBA) can greatly enhance Microsoft Excel® by giving users the ability to create their own functions within a worksheet and to create subroutines to perform repetitive actions. The book is written so readers are encouraged to experiment with VBA programming with examples using fairly simple physics or non-complicated mathematics such as root finding and numerical integration. Tested Excel® workbooks are available for each chapter and there is nothing to buy or install.
Author: Brian R. Kent
Publisher: Morgan & Claypool Publishers
ISBN: 1627059261
Category : Technology & Engineering
Languages : en
Pages : 176
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Book Description
SMath is a free mathematical notebook program similar to Mathcad that provides many options for studying and solving complex mathematical equations. This book is a primer providing a concise but thorough introduction that keeps physics at a fairly low leve
Author: Bernard V Liengme
Publisher: Morgan & Claypool Publishers
ISBN: 1681744619
Category : Science
Languages : en
Pages : 92
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Book Description
This book is both an introduction and a demonstration of how Visual Basic for Applications (VBA) can greatly enhance Microsoft Excel® by giving users the ability to create their own functions within a worksheet and to create subroutines to perform repetitive actions. The book is written so readers are encouraged to experiment with VBA programming with examples using fairly simple physics or non-complicated mathematics such as root finding and numerical integration. Tested Excel® workbooks are available for each chapter and there is nothing to buy or install.
Author: Brian Albright
Publisher: CRC Press
ISBN: 0429945051
Category : Business & Economics
Languages : en
Pages : 461
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Book Description
This text presents a wide variety of common types of models found in other mathematical modeling texts, as well as some new types. However, the models are presented in a very unique format. A typical section begins with a general description of the scenario being modeled. The model is then built using the appropriate mathematical tools. Then it is implemented and analyzed in Excel via step-by-step instructions. In the exercises, we ask students to modify or refine the existing model, analyze it further, or adapt it to similar scenarios.
Author: Hector Guerrero
Publisher: Springer
ISBN: 3030012794
Category : Business & Economics
Languages : en
Pages : 358
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Book Description
This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization. The second edition has been thoroughly revised: new topics, exercises and examples have been added, and the readability has been further improved. The book is primarily intended for students in business, economics and government, as well as professionals, who need a more rigorous introduction to business and data analytics – yet also need to learn the topic quickly and without overly academic explanations.
Author: Julio Cesar Rodriguez Martino
Publisher: Packt Publishing Ltd
ISBN: 178934512X
Category : Computers
Languages : en
Pages : 243
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Book Description
A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis. Key FeaturesUse Microsoft's product Excel to build advanced forecasting models using varied examples Cover range of machine learning tasks such as data mining, data analytics, smart visualization, and more Derive data-driven techniques using Excel plugins and APIs without much code required Book Description We have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel. The book starts by giving a general introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed. At the end of the book, the reader is presented with some advanced use cases using Automated Machine Learning, and artificial neural network, which simplifies the analysis task and represents the future of machine learning. What you will learnUse Excel to preview and cleanse datasetsUnderstand correlations between variables and optimize the input to machine learning modelsUse and evaluate different machine learning models from ExcelUnderstand the use of different visualizationsLearn the basic concepts and calculations to understand how artificial neural networks workLearn how to connect Excel to the Microsoft Azure cloudGet beyond proof of concepts and build fully functional data analysis flowsWho this book is for This book is for data analysis, machine learning enthusiasts, project managers, and someone who doesn't want to code much for performing core tasks of machine learning. Each example will help you perform end-to-end smart analytics. Working knowledge of Excel is required.
