Friends of CASM

Scientific Council

Members

Associate Members

Activities

Contact Us

The history of using auxiliary information in sample surveys is as old as the history of the applications of survey sampling. The works of Bowley (1926) and Neyman (1934,38), the foundation stones of  modern sampling theory, dealing with stratified random sampling and putting forward a theoretical criticism of non random sampling, may perhaps be referred to as the initial works, in the history of survey sampling, utilizing the auxiliary information. It was a general intuitive feeling of the survey statisticians, even during 1930’s, that the customary method of estimating the population mean or total of a variable of interest, may be improved if the information supplied by a related variable (auxiliary variable, supplementary variable, concomitant variable, ancillary variable or benchmark variable), say x is incorporated intelligibly in the estimation procedure. The work of Watson (1937) and Cochran (1940, 42) were the initial works to be worth mentioning here. Various research workers during the last 60 years confirm the view that in whatever form the auxiliary information be available, one may always utilize it to devise sampling strategies which are more efficient (if not uniformly then at least in a part of parametric space) than those in which no auxiliary information is utilized. In this two-day workshop demonstration will be given how use of the auxiliary information reduces the sampling error.

Venue: Lahore University of Management Sciences (LUMS), Lahore.

Resource Persons:

• Muhammad Hanif Mian (Lahore University of Management Sciences, Lahore)

• Zahoor Ahmed (University of Gujrat, Gujrat)

• Muhammad Qaiser Shahbaz (G C University, Lahore)