Sampling Techniques

  ~Ronit Bhowmick Christ University, Bengaluru.  Which sampling technique is a better population estimator, SRSWOR, or SRSWR? I tried logging the answer stepwise, in a way so that even someone who isn’t really connected to the statistics stream by any means can have a basic but broad picture of the topic. Here is how I am planning on dividing the entire topic: The definition of simple random sampling, the branches of simple random sampling with a numerical based example, definitions of sampling without replacement and sampling with replacement, the difference between both SRSWR and SRSWOR, notations and basic formulas, and finally I will also be showing the R codes that will conclude the difference. The definition: Simple random sampling (SRS) is defined as a sampling technique where every item in the population has an even chance and likelihood of being selected in the sample. Simple random sampling is a fundamental sampling method and can easily be a component of a more compl

  Two-stage cluster sampling                                                                - Rosma J Chackiath   INTRODUCTION Often it is impossible or impractical to create a sampling frame of a target population, and/or the target population is widely dispersed geographically, making data collection costs relatively high. Such situations are ideal for cluster sampling. Cluster sampling is a probability sampling procedure in which the researcher divides the population into separate groups called clusters.   A two-stage cluster sample design includes all the steps in a single-stage cluster sample design with one exception, the last step. Let us consider a population where individuals are clustered into groups.To do a two-stage cluster sampling, in the first step, we will do one-stage cluster sampling, i.e., we are going to select a few clusters randomly from the population. Instead of selecting all elements from these selected clusters into our sample as we did in the one-stage