what are the 3 types of sampling and what are they?

1. Simple Random Sampling: This is a type of sampling where every element in a population has an equal chance of being included in the sample. This type of sampling is commonly used when a researcher wants to make inferences based on a population but doesn't have the resources or time to collect data from all individuals in the population. 2. Stratified Sampling: Stratified sampling is a type of sampling where a population is divided into subgroups (known as strata) based on certain characteristics, and then a sample is taken from each subgroup. This method gives every stratum an equal chance of being represented in the sample, so the sample accurately reflects the population as a whole. 3. Cluster Sampling: Cluster sampling is a type of sampling where a large population is divided into smaller, more manageable clusters or groups, and then a sample is taken from each cluster or group. This type of sampling can be used when the population is too large or geographically dispersed to sample using the other methods. This type of sampling is cost effective and less time consuming than other sampling methods.