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Sinopsis: Sharon L. Lohr's SAMPLING: DESIGN AND ANALYSIS, 2ND EDITION, provides a modern introduction to the field of survey sampling intended for a wide audience of statistics students. Practical and authoritative, the book is listed as a standard reference for training on real-world survey problems by a number of prominent surveying organizations. Lohr concentrates on the statistical aspects of taking and analyzing a sample, incorporating a multitude of applications from a variety of disciplines. The text gives guidance on how to tell when a sample is valid or not, and how to design and analyze many different forms of sample surveys. Recent research on theoretical and applied aspects of sampling is included, as well as optional technology instructions for using statistical software with survey data.
Biografía del autor: Sharon Lohr (Ph.D. in statistics, University of Wisconsin-Madison) is the Thompson Industries Dean's Distinguished Professor of Statistics at Arizona State University, where she has taught since 1990. Dr. Lohr's research focuses on survey sampling, design of experiments, and applications of statistics to social sciences and education. She has published numerous articles in journals including The Annals of Statistics, Journal of the American Statistical Association, Journal of the Royal Statistical Society, Biometrika, Journal of Quantitative Criminology, Wisconsin Law Review, and The American Statistician. She has served as chair of the Survey Research Methods Section of the American Statistical Association, president of the Arizona Chapter of the American Statistical Association, Fellow of the American Statistical Association, Elected Member of the International Statistical Institute, and member of the Census Advisory Committee of Professional Associations and the Statistics Canada Advisory Board on Statistical Methodology. In 2003 she received the inaugural Gertrude M. Cox Award from the Washington Statistical Society and in 2009 was selected to present the Morris Hansen Lecture.
Título: Sampling: Design and Analysis (Advanced ...
Editorial: Duxbury Press
Condición del libro: Good
Descripción U.S.A.: Cengage Learning, 2009. Soft cover. Estado de conservación: New. 2nd Edition. Brand new book - nice international edition - fast delivery--. Nº de ref. de la librería ABE-15792265284
Descripción Estado de conservación: Good. Cover has some rubbing and edge wear. All items ship Mon-Fri. Nº de ref. de la librería 2Y68H3003JME
Descripción Cengage Learning, 2009. Hardcover. Estado de conservación: Good. Item may show signs of shelf wear. Pages may include limited notes and highlighting. Includes supplemental or companion materials if applicable. Access codes may or may not work. Connecting readers since 1972. Customer service is our top priority. Nº de ref. de la librería mon0000776604
Descripción Cengage Learning. Estado de conservación: Good. 0495105279 Used texts do not include any supplemental material such as access codes, info-trac, CDs, etc.All text is legible and may contain; markings, highlighting, bookstore stickers, worn corners, folded pages etc. Satisfaction Guaranteed. Orders ship same or next business day w/ tracking. Nº de ref. de la librería Z0495105279Z3
Descripción Duxbury Press, 2009. Hardcover. Estado de conservación: New. Nº de ref. de la librería SONG0495105279
Descripción Cengage Learning, 2009. Estado de conservación: Used. This Book is in Good Condition. Clean Copy With Light Amount of Wear. 100% Guaranteed. Summary: 1. INTRODUCTION. A Sample Controversy. Requirements of a Good Sample. Selection Bias. Measurement Error. Questionnaire Design. Sampling and Nonsampling Errors. 2. SIMPLE PROBABILITY SAMPLES. Types of Probability Samples. Framework for Probability Sampling. Simple Random Sampling. Sampling Weights. Confidence Intervals. Sample Size Estimation. Systematic Sampling. Randomization Theory Results for Simple Random Sampling. A Model for Simple Random Sampling. When Should a Simple Random Sample Be Used? Chapter Summary. 3. STRATIFIED SAMPLING. What is Stratified Sampling? Theory of Stratified Sampling. Sampling Weights. Allocating Observations to Strata. Defining Strata. A Model for Stratified Sampling. Poststratification. Quota Sampling. Chapter Summary. 4. RATIO AND REGRESSION ESTIMATION. Ratio Estimation. Regression Estimation. Estimation in Domains. Models for Ratio and Regression Estimation. Comparison. Chapter Summary. 5. CLUSTER SAMPLING WITH EQUAL PROBABILITIES. Notation for Cluster Sampling. One-Stage Cluster Sampling. Two-Stage Cluster Sampling. Using Weights in Cluster Samples. Designing a Cluster Sample. Systematic Sampling. Models for Cluster Sampling. Summary. Chapter Summary. 6. SAMPLING WITH UNEQUAL PROBABILITIES. Sampling One Primary Sampling Unit. One-Stage Sampling with Replacement. Two-Stage Sampling with Replacement. Unequal Probability Sampling Without Replacement. Examples of Unequal Probability Samples. Randomization Theory Results and Proofs. Models and Unequal Probability Sampling. Chapter Summary. 7. COMPLEX SURVEYS. Assembling Design Components. Sampling Weights. Estimating a Distribution Function. Plotting Data From a Complex Survey. Design Effects. The National Crime Victimization Survey. Sampling and Experiment Design. Chapter Summary. 8. NONRESPONSE. Effects of Ignoring Nonresponse. Designing Surveys to Reduce Nonsampling Errors. Callbacks and Two-Phase Sampling. Mechanisms for Nonresponse. Weighting Methods for Nonresponse. Imputation. Parametric Models for Nonresponse. What is An Acceptable Response Rate? Chapter Summary. 9. VARIANCE ESTIMATION IN COMPLEX SURVEYS. Linearization (Taylor Series) Methods. Random Group Methods. Resampling and Replication Methods. Generalized Variance Functions. Confidence Intervals. Chapter Summary. 10. CATEGORICAL DATA ANALYSIS IN COMPLEX SURVEYS. Chi-Squared Tests with Multinomial Sampling. Effects of Survey Design on Chi-Squared Tests. Corrections to Chi-Squared Tests. Loglinear Models. Chapter Summary. 11. REGRESSION WITH COMPLEX SURVEY DATA. Model-based Regression in Simple Random Samples. Regression in Complex Surveys. Should Weights be Used in Regression? Mixed Models for Cluster Samples. Logistic Regression. Generalized Regression Estimation for Population Totals. Chapter Summary. 12. TWO PHASE SAMPLING. Two-Phase Sampling for Stratification. Two-Phase Sampling for Ratio Estimation. Theory of Two-Phase Sampling. Chapter Summary. 13. ESTIMATING POPULATION SIZE. Capture-Recapture Estimates. Contingency Tables for Capture-Recapture Experiments. Assessing Undercoverage. Chapter Summary. 14. RARE POPULATIONS AND SMALL AREAS. What is a Rare Population? Sampling for Rare Events. Estimation in Domains, Revisited. Small Area Estimation. Chapter Summary. 15. SURVEY QUALITY. Coverage Error. Nonresponse Error. Measurement Error. Sensitive Questions. Processing Error. Sampling Error. Interaction of Error Sources. The Future of Sampling. Chapter Summary. Appendix A: The Survey Program. Appendix B: Probability Concepts Used in Sampling. Probability. Random Variables and Expected Value. Conditional Probability. Conditional Expectation. Appendix C: Data Sets. Appendix D: Computer Codes Used for Examples. Appendix E: Statistical Table. References. Author Index. Subject Index. Nº de ref. de la librería ABE_book_usedgood_0495105279
Descripción Duxbury Press, 2009. Hardcover. Estado de conservación: New. 2. Nº de ref. de la librería DADAX0495105279
Descripción Cengage Learning. Hardcover. Estado de conservación: Good. 0495105279 US Edition Textbook, May Have Highlights, Notes and/or Underlining, BOOK ONLY-NO ACCESS CODE, NO CD, Ships with Emailed Tracking from USA. Nº de ref. de la librería Z0495105279Z3
Descripción Duxbury Pr, 2009. Hardcover. Estado de conservación: Brand New. 2nd edition. 596 pages. 9.00x7.50x1.00 inches. In Stock. Nº de ref. de la librería 4-0495105279
Descripción Estado de conservación: Good. Sampling: Design and Analysis (Advanced Series). Nº de ref. de la librería SKU0091614