Dr. Scott Lynch has made a great job for those (like me) who want a clear introduction to the methods of bayesian data analysis. I hold a Ph.D. in plant breeding, and as many others, I was trained in the traditional frequentist approach for the analysis of experiments: linear regression, ANOVA and u
Introduction to Variance Estimation (Statistics for Social Science and Behavorial Sciences)
โ Scribed by Kirk Wolter
- Publisher
- Springer
- Year
- 2007
- Tongue
- English
- Leaves
- 462
- Edition
- 2nd
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Now available in paperback, this book is organized in a way that emphasizes both the theory and applications of the various variance estimating techniques. Results are often presented in the form of theorems; proofs are deleted when trivial or when a reference is readily available. It applies to large, complex surveys; and to provide an easy reference for the survey researcher who is faced with the problem of estimating variances for real survey data.
๐ SIMILAR VOLUMES
This book develops methods for two key problems in the analysis of large-scale surveys: dealing with incomplete data and making inferences about sparsely represented subdomains. The presentation is committed to two particular methods, multiple imputation for missing data and multivariate composition
Los Angeles: SAGE, 2012. - 496p.<div class="bb-sep"></div>This is a complete guide to statistics and SPSS for social science students. Statistics with SPSS for Social Science provides a step-by-step explanation of all the important statistical concepts, tests and procedures. It is also a guide to ge
Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal