Business Analytics: The Art of Modeling with Spreadsheets, EMEA Edition

Name: Business Analytics: The Art of Modeling with Spreadsheets, EMEA Edition
Price: 4490 ISK
Availability: InStock
Author: Stephen G. Powell; Kenneth R. Baker
ISBN: 9781119636946

Höfundar: Stephen G. Powell; Kenneth R. Baker (Útgáfa: 5)

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Now in its fifth edition, Powell and Baker's Business Analytics: The Art of Modeling with Spreadsheets provides students and business analysts with the technical knowledge and skill needed to develop real expertise in business modeling. In this book, the authors cover spreadsheet engineering, management science, and the modeling craft. The briefness & accessibility of this title offers opportunities to integrate other materials -such as cases -into the course.

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Útgefandi: Wiley Global Education UK

ISBN: 9781119636946

Print ISBN: 9781119586814

Format: ePub

Útgáfa: 5

Höfundar: Stephen G. Powell; Kenneth R. Baker

Tungumál: English

Útgefið: 01/2020

Prent takmörkun á líftíma: 100

Prent takmörkun: 10

Afritunar takmörkun: 2

Flokkar: Viðskiptafræði

Efnisflokkar: Viðskipti og hagfræði › Verkefnastjórnun

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COVER
TITLE PAGE
PREFACE
ABOUT THE AUTHORS
1 INTRODUCTION
1.1 MODELS AND MODELING
1.2 THE ROLE OF SPREADSHEETS
1.3 THE REAL WORLD AND THE MODEL WORLD
1.4 LESSONS FROM EXPERT AND NOVICE MODELERS
1.5 ORGANIZATION OF THE BOOK
1.6 SUMMARY
SUGGESTED READINGS
2 MODELING IN A PROBLEM‐SOLVING FRAMEWORK
2.1 INTRODUCTION
2.2 THE PROBLEM-SOLVING PROCESS
2.3 INFLUENCE CHARTS
2.4 CRAFT SKILLS FOR MODELING
2.5 SUMMARY
SUGGESTED READINGS
EXERCISES
3 SPREADSHEET ENGINEERING
3.1 INTRODUCTION
3.2 DESIGNING A SPREADSHEET
3.3 DESIGNING A WORKBOOK
3.4 BUILDING A WORKBOOK
3.5 TESTING A WORKBOOK
3.6 SUMMARY
SUGGESTED READINGS
EXERCISES
4 ANALYSIS USING SPREADSHEETS
4.1 INTRODUCTION
4.2 BASE-CASE ANALYSIS
4.3 WHAT-IF ANALYSIS
4.4 BREAKEVEN ANALYSIS
4.5 OPTIMIZATION ANALYSIS
4.6 SIMULATION AND RISK ANALYSIS
4.7 SUMMARY
EXERCISES
5 DATA EXPLORATION AND PREPARATION
5.1 INTRODUCTION
5.2 DATASET STRUCTURE
5.3 TYPES OF DATA
5.4 DATA EXPLORATION
5.5 DATA PREPARATION
5.6 SUMMARY
SUGGESTED READINGS
EXERCISES
6 CLASSIFICATION AND PREDICTION METHODS
6.1 INTRODUCTION
6.2 PRELIMINARIES
6.3 CLASSIFICATION AND PREDICTION TREES
6.4 ADDITIONAL ALGORITHMS FOR CLASSIFICATION
6.5 ADDITIONAL ALGORITHMS FOR PREDICTION
6.6 STRENGTHS AND WEAKNESSES OF ALGORITHMS
6.7 PRACTICAL ADVICE
6.8 SUMMARY
SUGGESTED READINGS
EXERCISES
7 SHORT-TERM FORECASTING
7.1 INTRODUCTION
7.2 FORECASTING WITH TIME-SERIES MODELS
7.3 THE EXPONENTIAL SMOOTHING MODEL
7.4 EXPONENTIAL SMOOTHING WITH A TREND
7.5 EXPONENTIAL SMOOTHING WITH TREND AND CYCLICAL FACTORS
7.6 USING XLMiner FOR SHORT-TERM FORECASTING
7.7 SUMMARY
SUGGESTED READINGS
EXERCISES
8 NONLINEAR OPTIMIZATION
8.1 INTRODUCTION
8.2 AN OPTIMIZATION EXAMPLE
8.3 BUILDING MODELS FOR SOLVER
8.4 MODEL CLASSIFICATION AND THE NONLINEAR SOLVER
8.5 NONLINEAR PROGRAMMING EXAMPLES
8.6 SENSITIVITY ANALYSIS FOR NONLINEAR PROGRAMS
8.7* THE PORTFOLIO OPTIMIZATION MODEL
8.8 SUMMARY
SUGGESTED READINGS
EXERCISES
9 LINEAR OPTIMIZATION
9.1 INTRODUCTION
9.2 ALLOCATION MODELS
9.3 COVERING MODELS
9.4 BLENDING MODELS
9.5 SENSITIVITY ANALYSIS FOR LINEAR PROGRAMS
9.6 PATTERNS IN LINEAR PROGRAMMING SOLUTIONS
9.7* DATA ENVELOPMENT ANALYSIS
9.8 SUMMARY
SUGGESTED READINGS
EXERCISES
APPENDIX 9.1 THE SOLVER SENSITIVITY REPORT
10 OPTIMIZATION OF NETWORK MODELS
10.1 INTRODUCTION
10.2 THE TRANSPORTATION MODEL
10.3 ASSIGNMENT MODEL
10.4 THE TRANSSHIPMENT MODEL
10.5 A STANDARD FORM FOR NETWORK MODELS
10.6 NETWORK MODELS WITH YIELDS
10.7 NETWORK MODELS FOR PROCESS TECHNOLOGIES
10.8 SUMMARY
EXERCISES
11 INTEGER OPTIMIZATION
11.1 INTRODUCTION
11.2 INTEGER VARIABLES AND THE INTEGER SOLVER
11.3 BINARY VARIABLES AND BINARY CHOICE MODELS
11.4 BINARY VARIABLES AND LOGICAL RELATIONSHIPS
11.5 THE FACILITY LOCATION MODEL
11.6 SUMMARY
SUGGESTED READINGS
EXERCISES
12 OPTIMIZATION OF NONSMOOTH MODELS
12.1 INTRODUCTION
12.2 FEATURES OF THE EVOLUTIONARY SOLVER
12.3 CURVE FITTING (REVISITED)
12.4 THE ADVERTISING BUDGET PROBLEM (REVISITED)
12.5 THE CAPITAL BUDGETING PROBLEM (REVISITED)
12.6 THE FIXED COST PROBLEM (REVISITED)
12.7 THE MACHINE-SEQUENCING PROBLEM
12.8 THE TRAVELING SALESPERSON PROBLEM
12.9 GROUP ASSIGNMENT
12.10 SUMMARY
EXERCISES
13 DECISION ANALYSIS
13.1 INTRODUCTION
13.2 PAYOFF TABLES AND DECISION CRITERIA
13.3 USING TREES TO MODEL DECISIONS
13.4 USING DECISION TREE SOFTWARE
13.5* MAXIMIZING EXPECTED UTILITY WITH DECISION TREE
13.6 SUMMARY
SUGGESTED READINGS
EXERCISES
14 MONTE CARLO SIMULATION
14.1 INTRODUCTION
14.2 A SIMPLE ILLUSTRATION
14.3 THE SIMULATION PROCESS
14.4 CORPORATE VALUATION USING SIMULATION
14.5 OPTION PRICING USING SIMULATION
14.6 SELECTING UNCERTAIN PARAMETERS
14.7 SELECTING PROBABILITY DISTRIBUTIONS
14.8 ENSURING PRECISION IN OUTPUTS
14.9 INTERPRETING SIMULATION OUTCOMES
14.10 WHEN TO SIMULATE AND WHEN NOT TO SIMULATE
14.11 SUMMARY
SUGGESTED READINGS
EXERCISES
15 OPTIMIZATION IN SIMULATION
15.1 INTRODUCTION
15.2 OPTIMIZATION WITH ONE OR TWO DECISION VARIABLES
15.3 STOCHASTIC OPTIMIZATION
15.4 CHANCE CONSTRAINTS
15.5 TWO‐STAGE PROBLEMS WITH RECOURSE
15.6 SUMMARY
SUGGESTED READINGS
EXERCISES
MODELING CASES
APPENDIX 1: BASIC EXCEL SKILLS
INTRODUCTION
EXCEL PREREQUISITES
THE EXCEL WINDOW
CONFIGURING EXCEL
MANIPULATING WINDOWS AND SHEETS
NAVIGATION
SELECTING CELLS
ENTERING TEXT AND DATA
EDITING CELLS
FORMATTING
BASIC FORMULAS
BASIC FUNCTIONS
CHARTING
PRINTING
HELP OPTIONS
KEYBOARD SHORTCUTS
CELL COMMENTS
NAMING CELLS AND RANGES
SOME ADVANCED TOOLS
APPENDIX 2: MACROS AND VBA
INTRODUCTION
RECORDING A MACRO
EDITING A MACRO
CREATING A USER-DEFINED FUNCTION
SUGGESTED READINGS
APPENDIX 3: BASIC PROBABILITY CONCEPTS
INTRODUCTION
PROBABILITY DISTRIBUTIONS
EXAMPLES OF DISCRETE DISTRIBUTIONS
EXAMPLES OF CONTINUOUS DISTRIBUTIONS
EXPECTED VALUES
CUMULATIVE DISTRIBUTION FUNCTIONS
TAIL PROBABILITIES
VARIABILITY
SAMPLING
INDEX
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