Handbook of Statistical Distributions with ApplicationsIn the area of applied statistics, scientists use statistical distributions to model a wide range of practical problems, from modeling the size grade distribution of onions to modeling global positioning data. To apply these probability models successfully, practitioners and researchers must have a thorough understanding of the theory as well as a |
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Contents
Preliminaries | 9 |
Discrete Uniform Distribution | 29 |
Binomial Distribution | 31 |
Hypergeometric Distribution | 51 |
Poisson Distribution | 71 |
Geometric Distribution | 93 |
Negative Binomial Distribution | 97 |
Logarithmic Series Distribution | 107 |
Logistic Distribution | 241 |
Lognormal Distribution | 247 |
Pareto Distribution | 257 |
Weibull Distribution | 263 |
Extreme Value Distribution | 269 |
Cauchy Distribution | 275 |
Inverse Gaussian Distribution | 281 |
Rayleigh Distribution | 289 |
Continuous Uniform Distribution | 115 |
Normal Distribution | 119 |
ChiSquare Distribution | 155 |
F Distribution | 163 |
Students t Distribution | 171 |
Exponential Distribution | 179 |
Gamma Distribution | 185 |
Beta Distribution | 195 |
Noncentral Chisquare Distribution | 207 |
Noncentral F Distribution | 217 |
Noncentral t Distribution | 225 |
Laplace Distribution | 233 |
Bivariate Normal Distribution | 293 |
Distribution of Runs | 307 |
Sign Test and Confidence Interval for the Median | 311 |
Wilcoxon SignedRank Test | 315 |
Wilcoxon RankSum Test | 319 |
Nonparametric Tolerance Interval | 323 |
Tolerance Factors for a Multivariate Normal Population | 325 |
Distribution of the Sample Multiple Correlation Coefficient | 329 |
335 | |
345 | |
Other editions - View all
Handbook of Statistical Distributions with Applications Kalimuthu Krishnamoorthy No preview available - 2006 |
Common terms and phrases
2-sided Algorithm Applications approximate binomial called Coefficient compute confidence interval confidence level correlation coefficient cumulative probability defective items defined degrees of freedom denote dialog box difference distribution function Enter the values equal error estimate evaluated exact Example expected expression Figure Furthermore gamma given goto greater independent indicate Inference integer least less Let X1 lognormal lower measurements Median method mode Moments normal distribution normal population normal random variable Note null hypothesis observed observed value one-sided p-value parameter percentiles plots Poisson population precision Properties proportion quantile Random Number random variable ratio rejected relation Results sample mean sample size sample sizes Solution specified standard deviation standard normal StatCalc statistic Suppose tail testing H0 tolerance limit trials true variance Variation
Popular passages
Page 343 - Estimation of the Mean of a Multivariate Normal Distribution," The Annals of Statistics 9, pp.