Sampling techniques: Sampling is the process

Sampling is the process of selecting a small group from a larger population to gather information and make conclusions about the whole group. It's a practical and cost-effective way to collect data, especially when studying when it is not possible. Learn about the different sampling methods in statistics, such as simple random sampling, systematic sampling, stratified sampling, clustered sampling, and non-probability sampling. Compare the advantages and disadvantages of each method with examples and diagrams. Statistics is an important aspect of Data Science. It helps make sense of the data at hand through various statistical techniques. However, multiple sampling techniques are employed to get the correct data. This article will answer questions like what is sampling, what is sampling in research, its importance, etc., and will teach you about sampling techniques, methods, types, uses, etc. Let us first start with understanding the basics. Sampling Method Types & Techniques: Sampling is the process of selecting a group of individuals from a population to study them and characterize them. Learn more about sampling techniques!