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A short introduction to Sampling Theory

A sample means selecting a small subset from a large set of data. Similarly, when we talk about the topic of sampling it means focusing on a small group and applying methods to find the various characteristics in common with the larger group. Choosing a small subset of people from the whole population and then using various statistical concepts of data analysis and interpretation for making predictions is called sampling theory. This topic involves the use of probability theory to analyses data samples and sampling theory helps in lowering down the costs and increase the speed of data collection. There are mainly two types of sampling theory one is probability sampling and another one is non-probability sampling.

Sampling theory is created to perform some tasks which are as follows:

Statistical estimation: For estimation of those constraints and parameters of a very large data such as the population. 

Testing of hypotheses: To find out if the chosen alternate hypothesis applies in the real word or not.

Statistical inference: finding whether certain generalizations made are correct or not '

Our Statistics assignment help service also provides homework solutions on the following subtopics of sampling theory as well.

  • Diversity sampling
  • Random sampling
  • Convenience sampling
  • Stratified sampling
  • Panel Sampling Theory-
  • Purposive sampling
  • Systematic sampling
  • Line intercept sampling
  • Modal instance sampling
  • Cluster random sampling
  • Matched random Sampling
  • Expert sampling
  • Multi-stage random sampling
  • Snowball sampling
  • Proportional and non-proportional quota sampling

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