Statistical survey design and evaluating impact / Tarun Kumar Roy, Rajib Acharya, Arun Kumar Roy.

By: Material type: TextTextCambridge : Cambridge University Press, 2016Description: xxiv, 262 pages 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
Subject(s): LOC classification:
  • HA 31.2 .R812 2016
Summary: Statistical designs, sample surveys and evaluation designs are fundamental tools for solving queries related to population parameters and the effects of public programs and policies. This book explores the concepts of effective sampling and evaluation techniques in a cohesive and concise manner. Sampling design techniques, including simple random sampling, stratified sampling, systematic sampling and cluster sampling, are presented in detail. These techniques play a vital role when choosing an appropriate sample survey design. The concepts of multistage design, non-sampling errors and evaluation techniques including before-after design, one-time treatment and control design are discussed extensively. The book focuses on different methods of estimation, including multiple regression analysis and logistic regression. It covers the issue of bias in a design, the source of such bias and ways to overcome it. Clear guidelines with remedial measures are outlined to facilitate choosing a suitable sampling design. --Amazon.co.uk
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Includes bibliographical references (pages 255-259) and index.

Statistical designs, sample surveys and evaluation designs are fundamental tools for solving queries related to population parameters and the effects of public programs and policies. This book explores the concepts of effective sampling and evaluation techniques in a cohesive and concise manner. Sampling design techniques, including simple random sampling, stratified sampling, systematic sampling and cluster sampling, are presented in detail. These techniques play a vital role when choosing an appropriate sample survey design. The concepts of multistage design, non-sampling errors and evaluation techniques including before-after design, one-time treatment and control design are discussed extensively. The book focuses on different methods of estimation, including multiple regression analysis and logistic regression. It covers the issue of bias in a design, the source of such bias and ways to overcome it. Clear guidelines with remedial measures are outlined to facilitate choosing a suitable sampling design. --Amazon.co.uk

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