Random samples refer to samples where every member of the population has an equal chance of being selected. This method helps ensure unbiased and representative data collection.
Imagine you have a jar filled with different colored candies. If you close your eyes, shake the jar, and randomly pick a candy without looking, you have taken a random sample of candies from the jar.
Simple Random Sampling: Simple random sampling is a method where each possible sample of a given size has an equal chance of being selected.
Stratified Sampling: Stratified sampling involves dividing the population into subgroups (strata) based on certain characteristics and then selecting samples from each stratum.
Cluster Sampling: Cluster sampling involves dividing the population into clusters or groups and randomly selecting entire clusters to include in the sample.
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