What is Sampling?
Researchers globally employ a strategic approach called sampling, where a small portion is selected from a larger population set. This method allows for the estimation of results that closely resemble what the entire population data set would give. This approach is efficient and saves researchers a significant amount of time and effort while providing results that are nearly identical. For instance, if you're interested in the preferences of people aged 25 to 35 in a district, you don’t have to survey the entire population. Instead, you can select a sample from a specific area, and this will give you an almost accurate estimation of the preferences of the whole population in that district.
Sampling Error
Researchers often use samples instead of studying an entire population. Sampling implicates randomly selecting a smaller group of data to represent the larger population. While this method is efficient, it's not perfect. The difference between the results obtained from the sample and the true values of the entire population is called sampling error. It's unavoidable because any sample is just an estimate of the whole.
While examining the entire population might eliminate sampling error, it's often impractical or even impossible. Sampling allows us to analyze large datasets efficiently and estimate population characteristics with a degree of accuracy.
Methods of Sampling
Probability Sampling: In probability sampling, every member of the population has a chance of being picked for the sample. This allows us to statistically generalize the results of our sample to the entire population. Some common probability sampling methods include:
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Simple Random Sampling
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Systematic Sampling
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Stratified Sampling
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Cluster Sampling
Non-Probability Sampling: In non-probability sampling, not every member of the population has an odds of being chosen for the sample. Thus, we cannot statistically generalize the results of our sample to the entire population. However, non-probability sampling methods can be helpful for experimental research or when it is not possible to get a probability sample. Different types of common non-probability sampling methods:
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Convenience Sampling
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Judgmental Sampling
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Snowball Sampling
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Quota Sampling
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