Sample Survey Theory: Some Pythagorean Perspectives
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
2003
|
| Schriftenreihe: | Springer Series in Statistics
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | This volume deals primarily with the classical question of how to draw conclusions about the population mean of a variable, given a sample with observations on that variable. Another classical question is how to use prior knowledge of an economic or definitional relationship between the population means of several variables, provided that the variables are observed in a sample. The present volume is a compilation of two discussion papers and some additional notes on these two basic questions. The discussion papers and notes were prepared for a 15-hour course at Statistics Netherlands in Voorburg in February 2000. The first discussion paper is entitled "A Memoir on Sampling and Rho, the Generalized Intrasample Correlation Coefficient" (1999). It describes a new approach to the problem of unequal probability sampling. The second discussion paper "The General Restriction Estimator" (2000), deals with the problem of how to find constrained estimators that obey a given set of restrictions imposed on the parameters to be estimated. Parts I and II of the volume provide a novel and systematic treatment of sampling theory considered from the angle of the sampling autocorrelation coefficient p (rho). The same concept plays an important role in the analysis of time series. Although this concept is also well known in sampling theory, for instance in cluster sampling and systematic sampling, generalizations of p for an arbitrary sampling design are to my knowledge not readily found in the literature |
| Beschreibung: | 1 Online-Ressource (XX, 420 p) |
| ISBN: | 9780387217642 9781441929884 |
| ISSN: | 0172-7397 |
| DOI: | 10.1007/978-0-387-21764-2 |
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Datensatz im Suchindex
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| spelling | Knottnerus, Paul Verfasser aut Sample Survey Theory Some Pythagorean Perspectives by Paul Knottnerus New York, NY Springer New York 2003 1 Online-Ressource (XX, 420 p) txt rdacontent c rdamedia cr rdacarrier Springer Series in Statistics 0172-7397 This volume deals primarily with the classical question of how to draw conclusions about the population mean of a variable, given a sample with observations on that variable. Another classical question is how to use prior knowledge of an economic or definitional relationship between the population means of several variables, provided that the variables are observed in a sample. The present volume is a compilation of two discussion papers and some additional notes on these two basic questions. The discussion papers and notes were prepared for a 15-hour course at Statistics Netherlands in Voorburg in February 2000. The first discussion paper is entitled "A Memoir on Sampling and Rho, the Generalized Intrasample Correlation Coefficient" (1999). It describes a new approach to the problem of unequal probability sampling. The second discussion paper "The General Restriction Estimator" (2000), deals with the problem of how to find constrained estimators that obey a given set of restrictions imposed on the parameters to be estimated. Parts I and II of the volume provide a novel and systematic treatment of sampling theory considered from the angle of the sampling autocorrelation coefficient p (rho). The same concept plays an important role in the analysis of time series. Although this concept is also well known in sampling theory, for instance in cluster sampling and systematic sampling, generalizations of p for an arbitrary sampling design are to my knowledge not readily found in the literature Statistics Mathematical statistics Statistical Theory and Methods Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law Statistik Korrelationskoeffizient (DE-588)4165345-2 gnd rswk-swf Schätzfunktion (DE-588)4431358-5 gnd rswk-swf Stichprobe (DE-588)4057502-0 gnd rswk-swf Stichprobe (DE-588)4057502-0 s Korrelationskoeffizient (DE-588)4165345-2 s 1\p DE-604 Schätzfunktion (DE-588)4431358-5 s 2\p DE-604 https://doi.org/10.1007/978-0-387-21764-2 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Knottnerus, Paul Sample Survey Theory Some Pythagorean Perspectives Statistics Mathematical statistics Statistical Theory and Methods Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law Statistik Korrelationskoeffizient (DE-588)4165345-2 gnd Schätzfunktion (DE-588)4431358-5 gnd Stichprobe (DE-588)4057502-0 gnd |
| subject_GND | (DE-588)4165345-2 (DE-588)4431358-5 (DE-588)4057502-0 |
| title | Sample Survey Theory Some Pythagorean Perspectives |
| title_auth | Sample Survey Theory Some Pythagorean Perspectives |
| title_exact_search | Sample Survey Theory Some Pythagorean Perspectives |
| title_full | Sample Survey Theory Some Pythagorean Perspectives by Paul Knottnerus |
| title_fullStr | Sample Survey Theory Some Pythagorean Perspectives by Paul Knottnerus |
| title_full_unstemmed | Sample Survey Theory Some Pythagorean Perspectives by Paul Knottnerus |
| title_short | Sample Survey Theory |
| title_sort | sample survey theory some pythagorean perspectives |
| title_sub | Some Pythagorean Perspectives |
| topic | Statistics Mathematical statistics Statistical Theory and Methods Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law Statistik Korrelationskoeffizient (DE-588)4165345-2 gnd Schätzfunktion (DE-588)4431358-5 gnd Stichprobe (DE-588)4057502-0 gnd |
| topic_facet | Statistics Mathematical statistics Statistical Theory and Methods Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law Statistik Korrelationskoeffizient Schätzfunktion Stichprobe |
| url | https://doi.org/10.1007/978-0-387-21764-2 |
| work_keys_str_mv | AT knottneruspaul samplesurveytheorysomepythagoreanperspectives |