Showing posts with label Data analysis. Show all posts
Showing posts with label Data analysis. Show all posts
Friday, September 28, 2007
Saturday, September 22, 2007
Sunday, September 16, 2007
Introduction to Probability with Statistical Applications
Publisher: Birkhäuser Boston; 1 editionLanguage: englishISBN: 0817644970Paperback: 328 pagesData: August 2007Format: PDFDescription: This textbook is an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. Main statistical concepts considered are point and interval estimates, hypothesis testing, power function, various statistical tests: z, t, chi-square and Kolmogorov-Smirnov.Key features:* Presents rigorous discussion, with definitions, theorems, and proofs, but aimed at a non-specialist audience;*Avoids linear algebra;* Treats informally the few unavoidable concepts from multivariable calculus, such as double integrals;* Motivates new concepts throughout using examples and brief conceptual discussions;* Develops basic ideas with clear definitions, carefully designed notation and techniques of statistical analysis, along with well-chosen examples, exercises and applications.The book contains enough material for two semesters but, with judicious selection, it can also be used for a one-semester course, either in probability and statistics or in probability alone. .Advanced undergraduate and graduate students in computer science, engineering, and other natural and social sciences with only a basic background in calculus will benefit from this introductory text balancing theory with applications.
Monday, August 6, 2007
Monte Carlo Simulation Using RiskSim
Click on the link above to download the pdf file
RiskSim is a Monte Carlo Simulation add-in for Microsoft Excel 97 (and later versions of Excel) forWindows and Macintosh.RiskSim provides random number generator functions as inputs for your model, automates MonteCarlo simulation, and creates charts. Your spreadsheet model may include various uncontrollableuncertainties as input assumptions (e.g., demand for a new product, uncertain variable cost ofproduction, competitor reaction), and you can use simulation to determine the uncertainty associatedwith the model's output (e.g., annual profit). RiskSim automates the simulation by trying hundreds ofwhat-ifs consistent with your assessment of the uncertainties.To use RiskSim, you(1) create a spreadsheet model(2) optionally use SensIt to identify critical inputs(3) enter one of RiskSim's random number generator functions in each input cell of your model(4) choose Tools Risk Simulation from Excel's menu3(5) specify the model output cell and the number of what-if trials(6) interpret RiskSim's histogram and cumulative distribution charts.RiskSim facilitates Monte Carlo simulation by providing:Nine random number generator functionsAbility to set the seed for random number generationAutomatic repeated sampling for simulationFrequency distribution of simulation resultsHistogram and cumulative distribution charts
RiskSim is a Monte Carlo Simulation add-in for Microsoft Excel 97 (and later versions of Excel) forWindows and Macintosh.RiskSim provides random number generator functions as inputs for your model, automates MonteCarlo simulation, and creates charts. Your spreadsheet model may include various uncontrollableuncertainties as input assumptions (e.g., demand for a new product, uncertain variable cost ofproduction, competitor reaction), and you can use simulation to determine the uncertainty associatedwith the model's output (e.g., annual profit). RiskSim automates the simulation by trying hundreds ofwhat-ifs consistent with your assessment of the uncertainties.To use RiskSim, you(1) create a spreadsheet model(2) optionally use SensIt to identify critical inputs(3) enter one of RiskSim's random number generator functions in each input cell of your model(4) choose Tools Risk Simulation from Excel's menu3(5) specify the model output cell and the number of what-if trials(6) interpret RiskSim's histogram and cumulative distribution charts.RiskSim facilitates Monte Carlo simulation by providing:Nine random number generator functionsAbility to set the seed for random number generationAutomatic repeated sampling for simulationFrequency distribution of simulation resultsHistogram and cumulative distribution charts
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