Why do Data Scientists use Sampling Funnel?
Introduction
In data science, sampling refers to the process of selecting a subset of data from a larger dataset for analysis. This subset, known as a sample, is chosen to represent the larger population from which it is drawn. There are various sampling techniques, each with its own advantages and applications.
Sampling is crucial in data science and forms a key topic in any Data Scientist Course because it allows analysts to work with manageable subsets of data, reducing computational complexity and processing time while still providing insights that generalise to the larger population. However, it is essential to choose an appropriate sampling method based on the research question, available resources, and characteristics of the data.
Types of Sampling
There are several types of...