Estimation of Finite Population Variance, Regression Coefficient

  • Parimal Mukhopadhyay
Part of the Lecture Notes in Statistics book series (LNS, volume 153)


In this chapter we consider estimation of a finite population variance and regression coefficient. The estimation of population variance is of considerable importance in many circumstances. The geneticsts often classify their population according to population variance [Thompson and Thoday (1979)]. In allocating sample size in a stratified random sampling according to optimum allocation rules, the stratum standard deviations are required to be estimated. Sections 5.2 through 5.4 consider design-based, model-based and Bayes prediction of a finite population variance. Section 5.5 considers some asymptotic properties of a sample regression coefficient. The next section considers pm-unbiased prediction of the slope parameter in the linear regression model. The concluding section addresses optimal prediction of the finite population regression coefficient under multiple regression model.


Unbiased Estimator Finite Population Linear Unbiased Predictor Good Linear Unbiased Estimator Superpopulation Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag New York, Inc. 2001

Authors and Affiliations

  • Parimal Mukhopadhyay
    • 1
  1. 1.Applied Statistics UnitIndian Statistical InstituteCalcuttaIndia

Personalised recommendations