Hi. This tutorial covers random and probability sampling.
When sampling from a population, it is important that the sample is selected randomly. Generally, a random sample will help produce a representative sample, which is the goal of sampling. A random sample is defined as a sample where every member of the population of interest has an equal chance of being selected for the sample.
So suppose you are interested in researching the following-- determining how many siblings a typical student has at a particular high school. Some may suggest that you simply walk around the hallways of the school and haphazardly ask students about their siblings.
This method of sampling is not random. Haphazard selection is not random selection because many students would not have a chance of being selected, especially those that are on other floors or wings of the school, or perhaps in a classroom and not in the hallway while the sample is being selected.
Since haphazard selection is not random selection, random sampling requires a probability sampling plan. And that is defined as a method that ensures a selection of a random sample. So going back to our example, we would need to write up some sort of plan where it's possible to select every single student in the school as part of our sample.
Random sampling will not always yield a representative sample. Generally it will, but not always. Really, essentially, it's when your sample size is small that you're not going to get that representative sample. But random sampling should always be considered first. And remember that a probability sampling plan must be taken before a random sample-- or sorry, excuse me, a probability sampling plan must be made before a random sample can be taken.
So that's your tutorial on random sampling. Thanks for watching.