Sampling is a little like going to the grocery store and plucking a nut or two to "sample" the product. While this might get you kicked out of your local grocery store in a research world it is encouraged to sample as much as you want!!!! No one will shun you for grabbing a handful of sample nuts as long as you share what you did! 🤯
It would be in most cases, except a few small populations, excruciatingly difficult to test everyone in the population. We then must consider a smaller and more reasonable size that "sort of" shared the same characteristics as the main population.
The risk in many of these cases is that sampling is done incorrectly and misrepresents the true population. To better ensure accuracy we may use a number different methods such as random and convenience samples. The video below gives a few ideas....
There is no such thing as an accurate sample! You can sample as much as you like, over and over, and it won't be 100% correct! Sampling in different ways by taking multiple measurements from different areas leads to better outcome.
Sometimes samples are not big enough to draw any real conclusions. Confidence levels and sample size calculations can help ensure a size of participants needed to make meaningful conclusions.
Likewise, how we design our study is going to have influence on the samples taken. Designs will impact how and what types of samples are needed and where we draw them from.
What we should learn here is that sampling is very important and if we desire to have studies that draw meaningful conclusions from the data some consideration over sampling is needed. Review your study design, access to samples, the selection and tools you will need to make a solid analysis of your study focus.
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