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Computational and Mathematical Modeling in the Social Sciences - Scott de Marchi
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Scott de Marchi:
Computational and Mathematical Modeling in the Social Sciences - Taschenbuch

2010, ISBN: 9780521619134

ID: 839594895

PHI Learning, 2010. Softcover. New. 18 x 24 cm. This book helps to solve business problems and to make better decisions. One can learn how to use Excel more effectively. Key Features of the book : • Model investment risks and returns • Analyze your sales team’s effectiveness • Create best, worst, and most-likely case scenarios • Compare lease vs. buy, and calculate loan terms • See how price, advertising, and seasonality affect sales • Managing inventory with precision • Quantify the value of customer loyalty • Calculate your break-even number and ROI • Maximize scheduling efficiency • Express “home-field advantage” in real numbers • Project company growth; predict election results, and more! • Plus—introduce yourself to PowerPivot for Excel Contents Introduction 1. What`s New in Excel 2010 2 Range Names 3 Lookup Functions 4 The INDEX Function 5 The MATCH Function 6 Text Functions 7 Dates and Date Functions 8 Evaluating Investments by Using Net Present Value Criteria 9 Internal Rate of Return 10 More Excel Financial Functions 11 Circular References 12 I F Statements 13 Time and Time Functions 14 The Paste Special Command 15 Three-Dimensional Formulas 16 The Auditing Tool 17 Sensitivity Analysis with Data Tables 18 The Goal Seek Command 19 Using the Scenario Manager for Sensitivity Analysis 20 The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK Functions 21 The SUMIF, AVERAGEIF, SUMIFS, and AVERAGEIFS Functions 22 The OFFSET Function 23 The INDIRECT Function 24 Conditional Formatting 25 Sorting in Excel 26 Tables 27 Spin Buttons, Scroll Bars, Option Buttons, Check Boxes, Combo Boxes, and Group List Boxes 28 An Introduction to Optimization with Excel Solver 29 Using Solver to Determine the Optimal Product Mix 30 Using Solver to Schedule Your Workforce 31 Using Solver to Solve Transportation or Distribution Problems 32 Using Solver for Capital Budgeting 33 Using Solver for Financial Planning 34 Using Solver to Rate Sports Teams 35 Warehouse Location and the GRG Multistart and Evolutionary Solver Engines 36 Penalties and the Evolutionary Solver 37 The Traveling Salesperson Problem 38 Importing Data from a Text File or Document 39 Importing Data from the Internet 40 Validating Data 41 Summarizing Data by Using Histograms 42 Summarizing Data by Using Descriptive Statistics 43 Using PivotTables and Slicers to Describe Data 44 Sparklines 45 Summarizing Data with Database Statistical Functions 46 Filtering Data and Removing Duplicates 47 Consolidating Data 48 Creating Subtotals 49 Estimating Straight Line Relationships 50 Modeling Exponential Growth 51 The Power Curve 52 Using Correlations to Summarize Relationship . 53 Introduction to Multiple Regression 54 Incorporating Qualitative Factors into Multiple Regression 55 Modeling Nonlinearities and Interactions 56 Analysis of Variance: One-Way ANOVA 57 Randomized Blocks and Two-Way ANOVA 58 Using Moving Averages to Understand Time Series 59 Winters`s Method 60 Ratio-to-Moving-Average Forecast Method 61 Forecasting in the Presence of Special Events 62 An Introduction to Random Variables 63 The Binomial, Hypergeometric, and Negative Binomial Random Variables 64 The Poisson and Exponential Random Variable 65 The Normal Random Variable 66 Weibull and Beta Distributions: Modeling Machine Life and Duration of a Project 67 Making Probability Statements from Forecasts 68 Using the Lognormal Random Variable to Model Stock Prices 69 Introduction to Monte Carlo Simulation 70 Calculating an Optimal Bid 71 Simulating Stock Prices and Asset Allocation Modeling 72 Fun and Games: Simulating Gambling and Sporting Event Probabilities 73 Using Resampling to Analyze Data 74 Pricing Stock Options 75 Determining Customer Value 76 The Economic Order Quantity Inventory Model 77 Inventory Modeling with Uncertain Demand 78 Queuing Theory: The Mathematics of Waiting in Line 79 Estimating a Demand Curve 80 Pricing Products by Printed Pages: 712., PHI Learning, 2010, Cambridge University Press, 2005. First edition. Softcover. New. Mathematical models in the social sciences have become increasingly sophisticated and widespread in the last decade. This period has also seen many critiques, most lamenting the sacrifices incurred in pursuit of mathematical rigor. If, as critics argue, our ability to understand the world has not improved during the mathematization of the social sciences, we might want to adopt a different paradigm. This book examines the three main fields of mathematical modeling - game theory, statistics, and computational methods - and proposes a new framework for modeling. Unlike previous treatments which view each field separately, the treatment provides a framework that spans and incorporates the different methodological approaches. The goal is to arrive at a new vision of modeling that allows researchers to solve more complex problems in the social sciences. Additionally, a special emphasis is placed upon the role of computational modeling in the social sciences. Contents 1. Not all fun and games: challenges in mathematical modeling 2. Looking for car keys without any street lights 3. From curses to complexity: the justification for computational modeling 4. Why everything should look like a nail: deriving parsimonious encodings for complex games 5. KKV redux: deriving and testing logical implications. Printed Pages: 219., Cambridge University Press, 2005

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Computational and Mathematical Modeling in the Social Sciences - Scott de Marchi
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
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Scott de Marchi:
Computational and Mathematical Modeling in the Social Sciences - Taschenbuch

2015, ISBN: 9780521619134

ID: 909255663

Cengage Learning India Pvt. Ltd, 2015. 4th edition. Softcover. New. David Poole’s innovative LINEAR ALGEBRA: A MODERN INTRODUCTION, 4e emphasizes a vectors approach and better prepares students to make the transition from computational to theoretical mathematics. Balancing theory and applications, the book is written in a conversational style and combines a traditional presentation with a focus on student-centered learning. Theoretical, computational, and applied topics are presented in a flexible yet integrated way. Stressing geometric understanding before computational techniques, vectors and vector geometry are introduced early to help students visualize concepts and develop mathematical maturity for abstract thinking. Additionally, the book includes ample applications drawn from a variety of disciplines, which reinforce the fact that linear algebra is a valuable tool for modeling real-life problems. Content: 1. VECTORS. Introduction: The Racetrack Game. The Geometry and Algebra of Vectors. Length and Angle: The Dot Product. Exploration: Vectors and Geometry. Lines and Planes. Exploration: The Cross Product. Writing Project: Origins of the Dot Product and the Cross Product. Applications. 2. SYSTEMS OF LINEAR EQUATIONS. Introduction: Triviality. Introduction to Systems of Linear Equations. Direct Methods for Solving Linear Systems. Writing Project: A History of Gaussian Elimination. Explorations: Lies My Computer Told Me; Partial Pivoting; Counting Operations: An Introduction to the Analysis of Algorithms. Spanning Sets and Linear Independence. Applications. Vignette: The Global Positioning System. Iterative Methods for Solving Linear Systems. 3. MATRICES. Introduction: Matrices in Action. Matrix Operations. Matrix Algebra. The Inverse of a Matrix. The LU Factorization. Subspaces, Basis, Dimension, and Rank. Introduction to Linear Transformations. Vignette: Robotics. Applications. 4. EIGENVALUES AND EIGENVECTORS. Introduction: A Dynamical System on Graphs. Introduction to Eigenvalues and Eigenvectors. Determinants. Writing Project: Which Came First-the Matrix or the Determinant? Vignette: Lewis Carroll’s Condensation Method. Exploration: Geometric Applications of Determinants. Eigenvalues and Eigenvectors of n x n Matrices. Writing Project: The History of Eigenvalues. Similarity and Diagonalization. Iterative Methods for Computing Eigenvalues. Applications and the Perron-Frobenius Theorem. Vignette: Ranking Sports Teams and Searching the Internet. 5. ORTHOGONALITY. Introduction: Shadows on a Wall. Orthogonality in Rn. Orthogonal Complements and Orthogonal Projections. The Gram-Schmidt Process and the QR Factorization. Explorations: The Modified QR Factorization; Approximating Eigenvalues with the QR Algorithm. Orthogonal Diagonalization of Symmetric Matrices. Applications. 6. VECTOR SPACES. Introduction: Fibonacci in (Vector) Space. Vector Spaces and Subspaces. Linear Independence, Basis, and Dimension. Writing Project: The Rise of Vector Spaces. Exploration: Magic Squares. Change of Basis. Linear Transformations. The Kernel and Range of a Linear Transformation. The Matrix of a Linear Transformation. Exploration: Tilings, Lattices and the Crystallographic Restriction. Applications. 7. DISTANCE AND APPROXIMATION. Introduction: Taxicab Geometry. Inner Product Spaces. Explorations: Vectors and Matrices with Complex Entries; Geometric Inequalities and Optimization Problems. Norms and Distance Functions. Least Squares Approximation. The Singular Value Decomposition. Vignette: Digital Image Compression. Applications. 8. CODES. (Online) Code Vectors. Vignette: The Codabar System. Error-Correcting Codes. Dual Codes. Linear Codes. The Minimum Distance of a Code. Appendix A: Mathematical Notation and Methods of Proof. Appendix B: Mathematical Induction. Appendix C: Complex Numbers. Appendix D: Polynomials. Printed Pages: 800., Cengage Learning India Pvt. Ltd, 2015, Cambridge University Press, 2005. First edition. Softcover. New. Mathematical models in the social sciences have become increasingly sophisticated and widespread in the last decade. This period has also seen many critiques, most lamenting the sacrifices incurred in pursuit of mathematical rigor. If, as critics argue, our ability to understand the world has not improved during the mathematization of the social sciences, we might want to adopt a different paradigm. This book examines the three main fields of mathematical modeling - game theory, statistics, and computational methods - and proposes a new framework for modeling. Unlike previous treatments which view each field separately, the treatment provides a framework that spans and incorporates the different methodological approaches. The goal is to arrive at a new vision of modeling that allows researchers to solve more complex problems in the social sciences. Additionally, a special emphasis is placed upon the role of computational modeling in the social sciences. Contents 1. Not all fun and games: challenges in mathematical modeling 2. Looking for car keys without any street lights 3. From curses to complexity: the justification for computational modeling 4. Why everything should look like a nail: deriving parsimonious encodings for complex games 5. KKV redux: deriving and testing logical implications. Printed Pages: 219., Cambridge University Press, 2005

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(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Computational and Mathematical Modeling in the Social Sciences - Scott de Marchi
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Scott de Marchi:
Computational and Mathematical Modeling in the Social Sciences - Taschenbuch

2015, ISBN: 9780521619134

ID: 1037651679

Cengage Learning India Pvt. Ltd, 2015. 4th edition. Softcover. New. David Poole’s innovative LINEAR ALGEBRA: A MODERN INTRODUCTION, 4e emphasizes a vectors approach and better prepares students to make the transition from computational to theoretical mathematics. Balancing theory and applications, the book is written in a conversational style and combines a traditional presentation with a focus on student-centered learning. Theoretical, computational, and applied topics are presented in a flexible yet integrated way. Stressing geometric understanding before computational techniques, vectors and vector geometry are introduced early to help students visualize concepts and develop mathematical maturity for abstract thinking. Additionally, the book includes ample applications drawn from a variety of disciplines, which reinforce the fact that linear algebra is a valuable tool for modeling real-life problems. Content: 1. VECTORS. Introduction: The Racetrack Game. The Geometry and Algebra of Vectors. Length and Angle: The Dot Product. Exploration: Vectors and Geometry. Lines and Planes. Exploration: The Cross Product. Writing Project: Origins of the Dot Product and the Cross Product. Applications. 2. SYSTEMS OF LINEAR EQUATIONS. Introduction: Triviality. Introduction to Systems of Linear Equations. Direct Methods for Solving Linear Systems. Writing Project: A History of Gaussian Elimination. Explorations: Lies My Computer Told Me; Partial Pivoting; Counting Operations: An Introduction to the Analysis of Algorithms. Spanning Sets and Linear Independence. Applications. Vignette: The Global Positioning System. Iterative Methods for Solving Linear Systems. 3. MATRICES. Introduction: Matrices in Action. Matrix Operations. Matrix Algebra. The Inverse of a Matrix. The LU Factorization. Subspaces, Basis, Dimension, and Rank. Introduction to Linear Transformations. Vignette: Robotics. Applications. 4. EIGENVALUES AND EIGENVECTORS. Introduction: A Dynamical System on Graphs. Introduction to Eigenvalues and Eigenvectors. Determinants. Writing Project: Which Came First-the Matrix or the Determinant? Vignette: Lewis Carroll’s Condensation Method. Exploration: Geometric Applications of Determinants. Eigenvalues and Eigenvectors of n x n Matrices. Writing Project: The History of Eigenvalues. Similarity and Diagonalization. Iterative Methods for Computing Eigenvalues. Applications and the Perron-Frobenius Theorem. Vignette: Ranking Sports Teams and Searching the Internet. 5. ORTHOGONALITY. Introduction: Shadows on a Wall. Orthogonality in Rn. Orthogonal Complements and Orthogonal Projections. The Gram-Schmidt Process and the QR Factorization. Explorations: The Modified QR Factorization; Approximating Eigenvalues with the QR Algorithm. Orthogonal Diagonalization of Symmetric Matrices. Applications. 6. VECTOR SPACES. Introduction: Fibonacci in (Vector) Space. Vector Spaces and Subspaces. Linear Independence, Basis, and Dimension. Writing Project: The Rise of Vector Spaces. Exploration: Magic Squares. Change of Basis. Linear Transformations. The Kernel and Range of a Linear Transformation. The Matrix of a Linear Transformation. Exploration: Tilings, Lattices and the Crystallographic Restriction. Applications. 7. DISTANCE AND APPROXIMATION. Introduction: Taxicab Geometry. Inner Product Spaces. Explorations: Vectors and Matrices with Complex Entries; Geometric Inequalities and Optimization Problems. Norms and Distance Functions. Least Squares Approximation. The Singular Value Decomposition. Vignette: Digital Image Compression. Applications. 8. CODES. (Online) Code Vectors. Vignette: The Codabar System. Error-Correcting Codes. Dual Codes. Linear Codes. The Minimum Distance of a Code. Appendix A: Mathematical Notation and Methods of Proof. Appendix B: Mathematical Induction. Appendix C: Complex Numbers. Appendix D: Polynomials. Printed Pages: 800., Cengage Learning India Pvt. Ltd, 2015, Cambridge University Press, 2005. First edition. Softcover. New. Mathematical models in the social sciences have become increasingly sophisticated and widespread in the last decade. This period has also seen many critiques, most lamenting the sacrifices incurred in pursuit of mathematical rigor. If, as critics argue, our ability to understand the world has not improved during the mathematization of the social sciences, we might want to adopt a different paradigm. This book examines the three main fields of mathematical modeling - game theory, statistics, and computational methods - and proposes a new framework for modeling. Unlike previous treatments which view each field separately, the treatment provides a framework that spans and incorporates the different methodological approaches. The goal is to arrive at a new vision of modeling that allows researchers to solve more complex problems in the social sciences. Additionally, a special emphasis is placed upon the role of computational modeling in the social sciences. Contents 1. Not all fun and games: challenges in mathematical modeling 2. Looking for car keys without any street lights 3. From curses to complexity: the justification for computational modeling 4. Why everything should look like a nail: deriving parsimonious encodings for complex games 5. KKV redux: deriving and testing logical implications. Printed Pages: 219., Cambridge University Press, 2005

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Computational and Mathematical Modeling in the Social Sciences - De Marchi, Scott
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De Marchi, Scott:
Computational and Mathematical Modeling in the Social Sciences - Taschenbuch

ISBN: 9780521619134

[ED: Softcover], [PU: CAMBRIDGE UNIV PR], Mathematical models in the social sciences have become increasingly sophisticated and widespread in the last decade. This period has also seen many critiques, most lamenting the sacrifices incurred in pursuit of mathematical rigor. If, as critics argue, our ability to understand the world has not improved during the mathematization of the social sciences, we might want to adopt a different paradigm. This book examines the three main fields of mathematical modeling - game theory, statistics, and computational methods - and proposes a new framework for modeling. Unlike previous treatments which view each field separately, the treatment provides a framework that spans and incorporates the different methodological approaches. The goal is to arrive at a new vision of modeling that allows researchers to solve more complex problems in the social sciences. Additionally, a special emphasis is placed upon the role of computational modeling in the social sciences. 220 pages - 20 line diagrams 7 tables Versandfertig in 2-4 Wochen, [SC: 0.00], Neuware, gewerbliches Angebot

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Computational and Mathematical Modeling in the Social Sciences - Scott De Marchi
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Scott De Marchi:
Computational and Mathematical Modeling in the Social Sciences - Taschenbuch

ISBN: 9780521619134

Paperback, [PU: CAMBRIDGE UNIVERSITY PRESS], Offers an overview of mathematical modeling concentrating on game theory, statistics and computational modeling., Social Theory

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Details zum Buch
Computational and Mathematical Modeling in the Social Sciences

Mathematical models in the social sciences have become increasingly sophisticated and widespread in the last decade. This period has also seen many critiques, most lamenting the sacrifices incurred in pursuit of mathematical rigor. If, as critics argue, our ability to understand the world has not improved during the mathematization of the social sciences, we might want to adopt a different paradigm. This book examines the three main fields of mathematical modeling - game theory, statistics, and computational methods - and proposes a new framework for modeling. Unlike previous treatments which view each field separately, the treatment provides a framework that spans and incorporates the different methodological approaches. The goal is to arrive at a new vision of modeling that allows researchers to solve more complex problems in the social sciences. Additionally, a special emphasis is placed upon the role of computational modeling in the social sciences.

Detailangaben zum Buch - Computational and Mathematical Modeling in the Social Sciences


EAN (ISBN-13): 9780521619134
ISBN (ISBN-10): 0521619130
Taschenbuch
Erscheinungsjahr: 2005
Herausgeber: CAMBRIDGE UNIV PR
220 Seiten
Gewicht: 0,308 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 31.05.2007 23:00:45
Buch zuletzt gefunden am 05.12.2017 12:02:01
ISBN/EAN: 0521619130

ISBN - alternative Schreibweisen:
0-521-61913-0, 978-0-521-61913-4


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