Stratified Sampling Explained
The scenario describes a situation where the population (farmers in a village) is divided into distinct subgroups or strata based on specific characteristics (marginal, small, and large farmers). A random sample is then selected from *each* of these subgroups.
Identifying the Sampling Method
This method of dividing the population into homogeneous groups (strata) and then drawing random samples from each stratum is known as Stratified Sampling.
- Population Division: Farmers are divided into marginal, small, and large categories. These categories act as the strata.
- Sampling within Strata: A random sample (20 farmers) is taken from *each* category.
- Goal: This ensures representation from all subgroups within the population.
Why Other Options Are Incorrect
- Systematic Sampling: Involves selecting every k-th element from an ordered list. This doesn't involve pre-dividing into specific categories like marginal, small, and large.
- Cluster Sampling: Involves dividing the population into clusters (often geographically), randomly selecting clusters, and then sampling individuals within those selected clusters. It doesn't guarantee sampling from *each* pre-defined farmer category.
- Multi-stage Sampling: This is a more complex process involving sampling in multiple stages, often combining other methods. While stratified sampling could be one stage, the description precisely fits the definition of stratified sampling itself.
Therefore, taking a random sample from each category (stratum) of farmers is a clear example of Stratified Sampling.
Important Questions from Sampling Techniques - Teaching
Homogenous subsets in the sampling are called
Match the LIST-I with LIST-II
LIST-I
Sampling frame
(Circles denotes unit selected)LIST-II
Sampling ProcedureA.
I. Systematic Sampling B.
II. Cluster Sampling C.
III. Simple Random Sampling D.
IV. Stratified Random Sampling
Choose the correct answer from the options given below:- To select an unbiased sample in statistical sense we need to make sure each unit has an ______ and ______ chance of selection.
- Theoretical sampling is used when.
A. Extension of the basic population is not known in advance
B. Features of the basic population are not known in advance
C. Sample Size is not defined in advance
D. Repeated drawing of sampling elements with criteria to be defined again in each step
E. Sampling is finished when the whole sample has been studied
Choose the correct answer from the options given below: - Which of the following is not a non-probability method of selecting samples from a population?
