Vijay Koshti Statistics ( Statistical concepts and related articles)

  1.3 Stratified Sampling   Introduction:   An important objective in any estimation problem is to obtain an estimator of a population parameter which can take care of the salient features of the population. If the population is homogeneous with respect to the characteristic under study, then the method of simple random sampling will yield a homogeneous sample, and in turn, the sample mean will serve as a good estimator of the population mean. Thus, if the population is homogeneous with respect to the characteristic under study, then the sample drawn through simple random sampling is expected to provide a representative sample. Moreover, the variance of the sample mean not only depends on the sample size and sampling fraction but also on the population variance. In order to increase the precision of an estimator, we need to use a sampling scheme which can reduce the heterogeneity in the population. If the population is heterogeneous with respect to the characteristic ...

  B. Sc. III Semester V Subject-Statistics-XI DSE-E15: Sampling Theory Theory: 36 Hours. (Credit 02)   Unit-1     Simple and Stratified Random Sampling: Introduction:         Sampling is quite often used in our day to day practical life. For example -   in a shop we assess the quality of sugar, wheat or any   other commodity by taking a handful of it from the bag and then decide to purchase it or not. A housewife normally tests, the cooked products to find if they are properly cooked and contain the proper quantity of salt. In sampling theory we first define the following terms. i)   Population (Universe) The group of individuals under study is called population or universe.   (The totality of the objects of study)   For example -if we are going to study the economic conditions of primary teachers in Maharashtra state, then the total of all the primary teachers in Maharashtra state is...