When you're conducting research about a group of individuals it's hardly possible for you to gather data on each and every person in the group. You would instead, take a sample. This sample is the group of people who will be participating in the research.
For you to draw legitimate conclusions from the results you obtain, you need to make a careful decision on how you'll select a sample that represents the group as a whole. Basically, you have two types of sampling techniques:
• Random sampling (probability sampling), which involves random selection that allows you to make statistical inferences about the entire group.
• Non-random sampling (non-probability sampling), which involves non-random selection based on criteria like the convenience that allows you to collect initial data easily.
Let's take a look at both.
Random Sampling
With random sampling, or probability sampling, you begin with a complete sample frame of all qualified people that have the same likelihood of being part of the chosen sample. The selection needs to occur "randomly", which means they don't differ in any substantial way from observations that aren't sampled. It's usually assumed the statistical testing contains information that has been collected through random sampling.
When you'd do it:
An example of when you'd do this type of sampling is exit polls from voters looking to predict an election's results.
Different types of random sampling online survey software are: • Simple random sampling
• Cluster sampling
• Stratified sampling
• Multi-stage sampling
Taking simple random sampling as an example, this type of sampling survey software is the most straightforward method of obtaining a random sample. Through this method, you pick the sample size you desire and select observations from the population in a manner that each observation has the same likelihood of selection until you achieve the desired sample size.
Non-Random Sampling
With this form of sampling survey tool, you exclude a certain amount of the population in the sample and you can't calculate that exact number. This means there are limits to the amount you can determine from the sample about the population.
When you'd do it:
Non-random sampling is used most often for exploratory studies such as pilot surveys (you deploy a survey tool to a smaller sample when you compare it to a predetermined sample size). This method is used in studies by researchers where it's impossible to draw random sampling because of cost and time considerations.
There are several types of non-random sampling such as:
• Quota sampling
• Convenience sampling
• Purposive sampling
• Snowball sampling
• Judgement sampling
Taking convenience sampling as an example, this is a non-random sampling method where samples are chosen from the population only because they're available conveniently to the researcher. These samples are chosen by researchers just because they're simple to recruit and the researchers don't consider choosing a sample that represents the whole population.
Now that you know the differences between the two, a few types of each, and some examples of how they're used, you can make an informed decision on which is best for your business.
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