Sampling involves selecting a subset of individuals from a population to estimate characteristics of the entire population. It is crucial for making inferences when it is impractical to study an entire population.
5 Must Know Facts For Your Next Test
A good sample should be representative of the population to avoid bias.
There are different types of sampling methods, including random, stratified, and cluster sampling.
The size of the sample can significantly impact the accuracy and reliability of the results.
Sampling error is the difference between the sample result and the true population result.
Non-sampling errors can occur due to data collection mistakes or non-responses.