**Estimating Mean Of A Normal Population Using Known Coefficient Of Variation**

**B.BHASKARA RAMA SARMA***

* Faculty of Mathematics , BRS Classes, #2-284,Vivekananda street,Hanumannagar,Ramavarappadu,Vijayawada,A.P-521108; Mobile:9441924418;e-mail:bbramasarma@yahoo.co.in

**ABSTRACT**

In estimating the parameters of a population if one can sacrifice the property of unbiasedness, better estimators in view of minimum mean squared error(MMSE) can be obtained.Consider a normal population N ( ) with mean and known coefficient of variation .Since the variance is a function of , it is appropriate if s is also considered along with the sample mean for estimating . Motivated by this observation, two estimators for are proposed in this paper using and s. The procedure adopted is based on that of Searle.D.T (1964). The large sample properties of these estimators and their comparison with that of the conventional estimator, i.e., sample mean , are also investigated. The corresponding results are presented. Larger gains are observed in efficiencies for small sample sizes.

**International
eJournal of Mathematics and Engineering**

Volume 1, Issue 4, Pages: 616 – 619