Simulation Methodology for Statisticians, Operations Analysts, and Engineers (1988)
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A01=Ed McKenzie
A01=P. W. A. Lewis
Age Group_Uncategorized
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Author_Ed McKenzie
Author_P. W. A. Lewis
automatic-update
Bias Elimination
Bivariate Exponential
Bivariate Histogram
Bivariate Normal
Bivariate Normal Random Variables
Bivariate Normal Sample
Bivariate Pair
Bivariate Random Variables
bootstrap resampling
Category1=Non-Fiction
Category=PB
Category=PBT
Common Random Numbers
Congruential Generator
COP=United Kingdom
Data
Delivery_Pre-order
Distribution Function
E. J. Orav
eq_isMigrated=2
eq_nobargain
Exploratory
exploratory data analysis
IBM PC
Jackknifed Estimator
Kurtosis Estimate
Language_English
Maximal Cycle Length
Monte Carlo methods
P. A. W. Lewis
PA=Temporarily unavailable
Price_€100 and above
Proportional Navigation
PS=Active
Pseudo-random Number Generation
Quantile Plots
Queueing Discipline
queueing theory
Random Permutations
Random Variables
Scatter Plots
Shift Register Generators
Simulation
simulation experiments in applied statistics
softlaunch
Statisticians
Systems
Triangular Kernel
Uniform Random Variables
variance reduction techniques
Product details
- ISBN 9781138105379
- Weight: 960g
- Dimensions: 185 x 234mm
- Publication Date: 02 Oct 2017
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
- Language: English
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Students of statistics, operations research, and engineering will be informed of simulation methodology for problems in both mathematical statistics and systems simulation. This discussion presents many of the necessary statistical and graphical techniques.
A discussion of statistical methods based on graphical techniques and exploratory data is among the highlights of Simulation Methodology for Statisticians, Operations Analysts, and Engineers.
For students who only have a minimal background in statistics and probability theory, the first five chapters provide an introduction to simulation.
