What is Systematic Sampling
Systematic sampling is a probability sampling technique in which members of a population are randomly selected and then grouped into a sample. However, the interval between each grouping must be fixed. The sampling interval is calculated by multiplying the population size by desired sample size. The sample population is selected in advance but systematic sampling can still be considered random if the interval is predetermined and the starting point random.
How to create a systematic sample
To create a systematic example, you can follow the steps below:
- Define the population: This is the group you will be sampling.
- Decide on the sample size : How much of the population do you need to sample to get an accurate idea?
- Give each member of the population their own number. If your group consists of 10,000 people, for example, begin by lining up the individuals and assigning them numbers.
- Determine the sampling interval This can be done by dividing population size by desired sample size.
- Select a starting point This is done by choosing a random number.
- Identify the members of your sample If you have a starting value of 15 and an interval of sample of 100, then the first member would be 115, and so on.
Different Types of Sampling
There are generally three ways to create a systematic sampling:
- Random sampling : A classic method of sampling in which the subject is chosen at predetermined intervals.
- Linear systematic sample: Instead of randomly selecting the sampling period, a skip pattern following a linear pathway is created.
- Circular systematic sample: After a sample has ended, it is repeated at the same location. 3
Systematic Sampling vs. Cluster Sampling
Cluster sampling is a method of sampling the population in a cluster. Cluster sampling divides the population into groups while systematic sampling creates a sample using fixed intervals.
A random sample of the population is selected, and then a fixed number of samples are taken at regular intervals from that population based on its size. Cluster sampling is the division of a population into groups and the random selection from each group.
The cluster sampling method is less precise than the other sampling methods. It can save money on the cost of obtaining a sampling. Cluster sampling is two-step procedure. This method is used when it’s difficult to compile a complete list of all the people. It may be difficult, for example, to create a list of all the customers in a grocery shop to interview.
A person can create a subset randomly selected of stores as the first step. Second, a random sampling of customers from those stores is interviewed. This simple manual process can save you time and money.