100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis By Gerard M. Verschuur

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100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis
 By Gerard M. Verschuur

100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis By Gerard M. Verschuur


100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis
 By Gerard M. Verschuur


PDF Ebook 100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis By Gerard M. Verschuur

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100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis
 By Gerard M. Verschuur

  • Amazon Sales Rank: #1438116 in Books
  • Brand: Holy Macro Books
  • Published on: 2016-11-01
  • Original language: English
  • Number of items: 1
  • Dimensions: 10.00" h x .50" w x 8.00" l, .0 pounds
  • Binding: Paperback
  • 213 pages
Features
  • Holy Macro Books

Review Having taught programming and computer science since 1963 and seen a myriad of textbooks, it is a real pleasure to get Dr G. M. Verschuurens book on EXCEL Simulation. It is definitely the best "Learn by examples" computer book I have ever seen.Ole Hebin, Prof. Emeritus (Univ. Copenhagen and Northwestern)------------------This book has an impressive breadth of examples from different areas. The writing is very straighforward and explanations seem very understandable for the beginning student. The companion website is an extraordinary resource!Dr. Bud Banis, Professor of Logistics, U. of Missouri, St. Louis

From the Inside Flap A revised book with 100 different simulationsI. GAMBLING

  • 1. THE DIE IS CAST
  • 2. CASTING SIX DICE
  • 3. FREQUENCIES
  • 4. GAMBLING STRATEGY
  • 5. ROULETTE MACHINE
  • 6. GAMBLER'S RUIN
  • 7. RANDOM WALK
  • 8. CRACKING A PASSWORD
II. STATISTICS
  • 9. A FAIR COIN
  • 10. THE MEAN OF MEANS
  • 11. SAMPLING
  • 12. THE NORMAL DISTRIBUTION
  • 13. NORMALIZING
  • 14. REPEATS
  • 15. CONFIDENCE MARGINS
  • 16. POWER CURVES
  • 17. HIDDEN PEAKS
  • 18. SAMPLING SIZES
  • 19. QUALITY CONTROL
III. GENETICS
  • 20. CHROMOSOMES
  • 21. SEX DETERMINATION
  • 22. RADIATION AND MUTATION
  • 23. MENDEL
  • 24. HARDY-WEINBERG LAW
  • 25. GENETIC DRIFT
  • 26. LETHAL HOMOZYGOTE
  • 27. REDUCED VITALITY
  • 28. TWO SELECTIVE FORCES
  • 29. BALANCED EQUILIBRIUM
  • 30. MOLECULAR CLOCK
  • 31. DNA SEQUENCING
IV. FINANCIAL
  • 32. FLUCTUATING APR
  • 33. RISK ANALYSIS
  • 34. MISSING/EXCEEDING TARGETS
  • 35. TWO-DIMENSIONAL FILTERS
  • 36. SCENARIOS
  • 37. MOVING AVERAGES
  • 38. RETURN ON INVESTMENT
  • 39. EMPLOYEE STOCK OPTIONS
  • 40. VALUE AT RISK
  • 41. ASIAN OPTIONS
  • 42. BLACK-SCHOLES MODEL
V. EXPANSION
  • 43. OFFSPRING OF TWO RABBITS
  • 44. EXTRAPOLATION
  • 45. PREDATOR-PREY CYCLE
  • 46. HOMEOSTASIS
  • 47. TAKING MEDICATION
  • 48. POPULATION PYRAMID
  • 49. TITRATION
  • 50. EC50 DETERMINATION
  • 51. CONVERTER
  • 52. CONDITIONAL TRAINING
  • 53. EPIDEMICS
VI. MONTE CARLO SIMULATIONS
  • 54. HOW RANDOM IS RANDOM
  • 55. BROWNIAN MOTION
  • 56. A TRAFFIC SITUATION
  • 57. UNCERTAINTIES IN SALES
  • 58. EXCHANGE RATE FLUCTUATIONS
  • 59. COST ESTIMATES
  • 60. MARKET GROWTH
  • 61. INTEGRATION W/ MONTE CARLO
VII. ITERATIONS
  • 62. CIRCULAR REFERENCES
  • 63. COUNTING NEW HITS
  • 64. CIRCULAR GRADIENTS
  • 65. SINGLE-CELL ARRAYS
  • 66. MULTI-CELL ARRAYS
  • 67. SOLVING EQUATIONS
  • 68. LEAST SQUARES METHOD
  • 69. COMBINING SCENARIOS
  • 70. LOGISTICS
VIII. EXTRAS
  • 71. AREA CODE FINDER
  • 72. GRAPH MANIPULATION
  • 73. DETECTING OUTLIERS
  • 74. FALSE POSITIVES
  • 75. PROBABILITY OF BELIEFS
  • 76. UNBIASED SAMPLING
  • 77. NUMBERING RECORDS
  • 78. FISCAL YEAR
  • 79. STOCK MARKET
  • 80. WEATHER FORECAST
IX. MISCELLANEA
  • 81. DATA TABLE WITH MEMORY
  • 82. GRAPH MANIPULATION
  • 83. SIMULATION OF A SLOT MACHINE
  • 84. LETTER GAME
  • 85. A HAWK-DOVE SIMULATION
  • 86. FLOCK BEHAVIOR
  • 87. SIMULATION OF SICK CASES
  • 88. EHRENFEST'S URN SIMULATION
  • 89. TWO MONTE CARLO INTEGRATIONS
  • 90. RANDOMNESS IN GENE POOLS
  • 91. RANDOM MATING
  • 92. DIFFERENCES IN FITNESS
  • 93. LOAN SIMULATION
  • 94. STOCK VOLATILITY
  • 95. S&P 500 PERFORMANCE
  • 96. SCENARIO RISKS
  • 97. TEMPERATURE FLUCTUATIONS
  • 98. JUROR SELECTION
  • 99. WAITING TIME SIMULATION
  • 100.PROJECT DELAYS
X. APPENDICES
  • 1. LOCKING CELL REFERENCES
  • 2. NESTED FUNCTIONS
  • 3. WHAT-IF TABLES
  • 4. MONTE CARLO SIMULATIONS
  • 5. SIMULATION CONTROLS
X. INDEX

About the Author Gerard M. Verschuuren, PhD, is a Microsoft Certified Professional specializing in C#.NET, VB, VBA, and VB.NET. He is the principal of Genesis PC, where he teaches and advises on the use of curve-fitting software such as Excel and XLfit in data, regression, and statistical analyses. His clients include Abbott, Bose, IBM, Liberty Mutual, Massachusetts General Hospital, and Harvard University. He is the author of numerous computer programming books, including Excel for Scientists, Excel VBA, From VBA to VSTO, Access VBA. He lives in southern New Hampshire.

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100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis By Gerard M. Verschuur PDF

100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis By Gerard M. Verschuur PDF
100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis By Gerard M. Verschuur PDF

100 Excel Simulations: Using Excel to Model Risk, Investments, Genetics, Growth, Gambling and Monte Carlo Analysis By Gerard M. Verschuur


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