Advanced Sampling Theory With Applications: How Michael ""Selected"" AmySpringer Science & Business Media, 2003 - 1218 páginas Advanced Sampling Theory with Applications: How Michael 'selected' Amy is a comprehensive expose of basic and advanced sampling techniques along with their applications in the diverse fields of science and technology. |
Índice
BASIC CONCEPTS AND MATHEMATICAL | 1 |
PURPOSE | 2 |
SIMPLE | 3 |
MULTISTAGE SUCCESSIVE AND RESAMPLING | 10 |
NONRESPONSE AND ITS TREATMENTS | 12 |
SIMPLE RANDOM SAMPLING | 50 |
1 | 56 |
Simple random sampling with replacement | 71 |
7 | 123 |
STRATIFIED AND POSTSTRATIFIED SAMPLING | 137 |
BIBLIOGRAPHY | 212 |
PROBABILITY | 295 |
MISCELLANEOUS TOPICS | 349 |
APPENDIX | 521 |
MULTIPHASE SAMPLING | 529 |
AUTHOR INDEX | 534 |
Otras ediciones - Ver todo
Advanced Sampling Theory with Applications: How Michael 'selected ..., Volumen 1 Sarjinder Singh No hay ninguna vista previa disponible - 2003 |
Advanced Sampling Theory with Applications: How Michael 'selected ..., Volumen 1 Sarjinder Singh No hay ninguna vista previa disponible - 2003 |
Términos y frases comunes
auxiliary variable average number bias calibration class of estimators confidence interval estimate Construct 95 continuous random variable cumulative distribution function defined denote discrete random variable distinct units estate farm loans Estimate the average estimator of population estimator of variance example expected value Find finite population variance following theorems Hence the theorem Hint ith unit linear regression estimator mean squared error mean Ỹ median method nonreal estate farm number of fish number of units obtain order of approximation P₁ population mean population parameter population proportion population total possible samples PPSWR Proof Pseudo-Random Number PRN ratio estimator real estate farm relative efficiency relative standard error replacement sampling sample mean sample variances sampling scheme Select a sample simple random sampling Singh species group SRSWOR sampling study variable total number unbiased estimator usual estimator Y₁ Σ Σ ΣΥ