Statistics in Survey Sampling

Regular price €100.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Jae Kwang Kim
analytic inference techniques
Author_Jae Kwang Kim
auxiliary data integration
Bayesian
Category=GPH
Category=GPS
Category=JHBC
Category=JMB
Category=PBT
cluster
design-based inference
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
estimation
frequentist estimation
graduate level survey methodology
imputation
model-assisted survey analysis
probability sampling methods
stratified
two-phase
variance

Product details

  • ISBN 9781032997766
  • Weight: 690g
  • Dimensions: 178 x 254mm
  • Publication Date: 29 Sep 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

Statistics in Survey Sampling offers a comprehensive and rigorous introduction to the principles and practices of survey sampling. Bridging the gap between statistical theory and real-world data collection, this textbook presents both classical methods and modern developments, equipping readers with the tools to design effective surveys and make reliable inferences from sample data.

With a strong foundation in design-based inference and frequentist methodology, the book emphasizes representativeness, efficiency, and the integration of auxiliary information in estimation procedures. It also introduces emerging research topics that reflect the evolving landscape of data collection and analysis.

Key Features:

  • Rigorous treatment of statistical theory for design-based inference in probability sampling
  • Thorough exploration of model-assisted estimation techniques using auxiliary data
  • Coverage of modern topics including data integration, analytic inference, predictive inference, and voluntary sample analysis
  • Detailed examples illustrate the methods throughout the book
  • Focused development within the frequentist framework, with limited emphasis on Bayesian or nonparametric methods
  • Exercises in all chapters enable use as a course text or for self-study
  • Includes appendices on key background topics such as asymptotic theory and projection techniques

This textbook is ideal for graduate students in statistics with prior courses in statistical theory and linear models. It is also a valuable reference for researchers and practitioners engaged in survey design, public policy evaluation, official statistics, and data science applications involving sample-based inference.

Jae Kwang Kim is the LAS Dean’s Professor in the Department of Statistics at Iowa State University. He is a fellow of American Statistical Association (ASA) and Institute of Mathematical Statistics (IMS). He is the recipient of the 2015 Gertude M. Cox award, sponsored by the Washington Statistical Society and RTI international.

More from this author