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Author: Christopher Teh Boon Sung
Publisher: Universal-Publishers
ISBN: 1627340386
Category : Technology & Engineering
Languages : en
Pages : 350
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Book Description
This book is for agriculturists, many of whom are either novices or non-computer programmers, about how they can build their mathematical models in Microsoft Excel. Of all modeling platforms, spreadsheets like Excel require the least proficiency in computer programming. This book introduces an Excel add-in called BuildIt (available for free as download) that shields users from having to use Excel's VBA (Visual Basic for Applications) programming language and yet allows agriculturists to build simple to large complex models without having to learn complicated computer programming techniques or to use sophisticated Excel techniques. This book first discusses how BuildIt works and how it is used to build models. Examples range from the simple to progressively more complex mathematical models. Ultimately, readers are taught how to build a generic crop growth model from its five core components: meteorology, canopy photosynthesis, energy balance, soil water, and crop growth development. Ultimately, agriculturists will be able to build their own mathematical models in Excel and concentrate more on the science and mathematics of their modeling work rather than being distracted by the intricacies of computer programming.
Author: Christopher Teh Boon Sung
Publisher: Universal-Publishers
ISBN: 1627340386
Category : Technology & Engineering
Languages : en
Pages : 350
Get Book Here
Book Description
This book is for agriculturists, many of whom are either novices or non-computer programmers, about how they can build their mathematical models in Microsoft Excel. Of all modeling platforms, spreadsheets like Excel require the least proficiency in computer programming. This book introduces an Excel add-in called BuildIt (available for free as download) that shields users from having to use Excel's VBA (Visual Basic for Applications) programming language and yet allows agriculturists to build simple to large complex models without having to learn complicated computer programming techniques or to use sophisticated Excel techniques. This book first discusses how BuildIt works and how it is used to build models. Examples range from the simple to progressively more complex mathematical models. Ultimately, readers are taught how to build a generic crop growth model from its five core components: meteorology, canopy photosynthesis, energy balance, soil water, and crop growth development. Ultimately, agriculturists will be able to build their own mathematical models in Excel and concentrate more on the science and mathematics of their modeling work rather than being distracted by the intricacies of computer programming.
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: J. Holton Wilson
Publisher: Business Expert Press
ISBN: 160649435X
Category : Business & Economics
Languages : en
Pages : 144
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Book Description
The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. This book will teach you the essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The authors take a non-theoretical treatment that is accessible even if you have a limited statistical background. It is specifically designed to teach the correct use of regression, while advising you of its limitations and teaching about common pitfalls. This book describes exactly how regression models are developed and evaluated —where real data is used, instead of contrived textbook-like problems. Completing this book will allow you to understand and build basic business/economic models using regression analysis. You will be able to interpret the output of those models and you will be able to evaluate the models for accuracy and shortcomings. Even if you never build a model yourself, at some point in your career it is likely that you will find it necessary to interpret one; this book will make that possible. Included are instructions for using Microsoft Excel to build business/economic models using regression analysis with an appendix using screen shots and step-by-step instructions.
Author: Kenneth R. Baker
Publisher: John Wiley & Sons
ISBN: 1118008979
Category : Business & Economics
Languages : en
Pages : 431
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Book Description
Reflects the latest applied research and features state-of-the-art software for building and solving spreadsheet optimization models Thoroughly updated to reflect the latest topical and technical advances in the field, Optimization Modeling with Spreadsheets, Second Edition continues to focus on solving real-world optimization problems through the creation of mathematical models and the use of spreadsheets to represent and analyze those models. Developed and extensively classroom-tested by the author, the book features a systematic approach that equips readers with the skills to apply optimization tools effectively without the need to rely on specialized algorithms. This new edition uses the powerful software package Risk Solver Platform (RSP) for optimization, including its Evolutionary Solver, which employs many recently developed ideas for heuristic programming. The author provides expanded coverage of integer programming and discusses linear and nonlinear programming using a systematic approach that emphasizes the use of spreadsheet-based optimization tools. The Second Edition also features: Classifications for the various problem types, providing the reader with a broad framework for building and recognizing optimization models Network models that allow for a more general form of mass balance A systematic introduction to Data Envelopment Analysis (DEA) The identification of qualitative patterns in order to meaningfully interpret linear programming solutions An introduction to stochastic programming and the use of RSP to solve problems of this type Additional examples, exercises, and cases have been included throughout, allowing readers to test their comprehension of the material. In addition, a related website features Microsoft Office® Excel files to accompany the figures and data sets in the book. With its accessible and comprehensive presentation, Optimization Modeling with Spreadsheets, Second Edition is an excellent book for courses on deterministic models, optimization, and spreadsheet modeling at the upper-undergraduate and graduate levels. The book can also serve as a reference for researchers, practitioners, and consultants working in business, engineering, operations research, and management science.
Author: William P. Fox
Publisher: CRC Press
ISBN: 1000388867
Category : Mathematics
Languages : en
Pages : 573
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Book Description
Mathematical modeling is both a skill and an art and must be practiced in order to maintain and enhance the ability to use those skills. Though the topics covered in this book are the typical topics of most mathematical modeling courses, this book is best used for individuals or groups who have already taken an introductory mathematical modeling course. This book will be of interest to instructors and students offering courses focused on discrete modeling or modeling for decision making.
Author: Michael Rees
Publisher: John Wiley & Sons
ISBN: 1118904001
Category : Business & Economics
Languages : en
Pages : 546
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Book Description
The comprehensive, broadly-applicable, real-world guide to financial modelling Principles of Financial Modelling – Model Design and Best Practices Using Excel and VBAcovers the full spectrum of financial modelling tools and techniques in order to provide practical skills that are grounded in real-world applications. Based on rigorously-tested materials created for consulting projects and for training courses, this book demonstrates how to plan, design and build financial models that are flexible, robust, transparent, and highly applicable to a wide range of planning, forecasting and decision-support contexts. This book integrates theory and practice to provide a high-value resource for anyone wanting to gain a practical understanding of this complex and nuanced topic. Highlights of its content include extensive coverage of: Model design and best practices, including the optimisation of data structures and layout, maximising transparency, balancing complexity with flexibility, dealing with circularity, model audit and error-checking Sensitivity and scenario analysis, simulation, and optimisation Data manipulation and analysis The use and choice of Excel functions and functionality, including advanced functions and those from all categories, as well as of VBA and its key areas of application within financial modelling The companion website provides approximately 235 Excel files (screen-clips of most of which are shown in the text), which demonstrate key principles in modelling, as well as providing many examples of the use of Excel functions and VBA macros. These facilitate learning and have a strong emphasis on practical solutions and direct real-world application. For practical instruction, robust technique and clear presentation, Principles of Financial Modelling is the premier guide to real-world financial modelling from the ground up. It provides clear instruction applicable across sectors, settings and countries, and is presented in a well-structured and highly-developed format that is accessible to people with different backgrounds.
Author: Jeffrey H. Moore
Publisher: Pearson Educacion
ISBN: 9780131218512
Category : Business policy
Languages : en
Pages : 693
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Book Description
CD-ROM contains: Premium Solver for Education -- Solver Table add-in software -- Extend LT 4.0 (simulation software) -- TreePlan -- GLP, a graphic visualization program -- Excel templates for in-text examples.
Author: William P. Fox
Publisher: CRC Press
ISBN: 1351368230
Category : Business & Economics
Languages : en
Pages : 336
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Book Description
Mathematical Modeling for Business Analytics is written for decision makers at all levels. This book presents the latest tools and techniques available to help in the decision process. The interpretation and explanation of the results are crucial to understanding the strengths and limitations of modeling. This book emphasizes and focuses on the aspects of constructing a useful model formulation, as well as building the skills required for decision analysis. The book also focuses on sensitivity analysis. The author encourages readers to formally think about solving problems by using a thorough process. Many scenarios and illustrative examples are provided to help solve problems. Each chapter is also comprehensively arranged so that readers gain an in-depth understanding of the subject which includes introductions, background information and analysis. Both undergraduate and graduate students taking methods courses in methods and discrete mathematical modeling courses will greatly benefit from using this book. Boasts many illustrative examples to help solve problems Provides many solutions for each chapter Emphasizes model formulation and helps create model building skills for decision analysis Provides the tools to support analysis and interpretation
Author: Sandip Banerjee
Publisher: CRC Press
ISBN: 1351022938
Category : Mathematics
Languages : en
Pages : 419
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Book Description
Mathematical Modeling: Models, Analysis and Applications, Second Edition introduces models of both discrete and continuous systems. This book is aimed at newcomers who desires to learn mathematical modeling, especially students taking a first course in the subject. Beginning with the step-by-step guidance of model formulation, this book equips the reader about modeling with difference equations (discrete models), ODE’s, PDE’s, delay and stochastic differential equations (continuous models). This book provides interdisciplinary and integrative overview of mathematical modeling, making it a complete textbook for a wide audience. A unique feature of the book is the breadth of coverage of different examples on mathematical modelling, which include population models, economic models, arms race models, combat models, learning model, alcohol dynamics model, carbon dating, drug distribution models, mechanical oscillation models, epidemic models, tumor models, traffic flow models, crime flow models, spatial models, football team performance model, breathing model, two neuron system model, zombie model and model on love affairs. Common themes such as equilibrium points, stability, phase plane analysis, bifurcations, limit cycles, period doubling and chaos run through several chapters and their interpretations in the context of the model have been highlighted. In chapter 3, a section on estimation of system parameters with real life data for model validation has also been discussed. Features Covers discrete, continuous, spatial, delayed and stochastic models. Over 250 illustrations, 300 examples and exercises with complete solutions. Incorporates MATHEMATICA® and MATLAB®, each chapter contains Mathematica and Matlab codes used to display numerical results (available at CRC website). Separate sections for Projects. Several exercise problems can also be used for projects. Presents real life examples of discrete and continuous scenarios. The book is ideal for an introductory course for undergraduate and graduate students, engineers, applied mathematicians and researchers working in various areas of natural and applied sciences.
Author: Stephen DeMeo
Publisher: Educe NY
ISBN: 0983712069
Category : Education
Languages : en
Pages : 385
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Book Description
Global warming, our current and greatest challenge, is without precedent. Among the many consequences that are impacting our society, one unanticipated concern involves scientific truth. When the President of the United States, and others in his administration, declare that global warming is fake science, it calls into question what real science is and what real school science should be. I will argue that real science is quality science, one that is based on the rigorous collection of reliable and valid data. To collect quality data requires bending over backwards to get things right, and this is exactly what makes science so special. Truth is made when scientists go this extra yard and devise controlled experiments, collect large data sets, confirm the data, and rationally analyze their results. Making scientific truth sounds difficult to do in the science laboratory, but in reality, there are many straightforward ways that truth can be constructed. In the first of two volumes, I discuss twelve such ways – I call them Confidence Indicators – that can allow students to strongly believe in their data and their subsequent results. Many of these methods are intuitive and can be used by young students on the late elementary level all the way up to those taking introductory college science courses. As in life, science is not without doubt. In the second volume I introduce the concept of scientific uncertainty and the indicators used to calculate its magnitude. I will show that science is about connecting confidence with uncertainty in a specific manner, what I refer to as the Confidence-Uncertainty Continuum expression. This important relationship epitomizes the scientific enterprise as a search for probabilistic rather than absolute truth. This two-volume set will contain a variety of ways that data quality can be instituted into a science curriculum. To support its use, many of the examples that I will present involve science teachers as well as student work and feedback from different grade levels and in different scientific disciplines. Specific chapters will be devoted to reviewing the academic literature on data quality as well as describing my own personal research on this important but often neglected topic.
