Systematic Sampling:
Systematic sampling is a probability sampling method in which the sample is chosen from a target population by selecting a random starting point and selecting other members after a fixed ‘sampling interval’. This sampling interval is calculated by dividing the population size by the desired sample size.
Example:
A local NGO is seeking to form a systematic sample of 500 volunteers from a population of 5000, they can select every 10th person (5000/500 = 10) in the population to systematically form a sampling interval.
Systematic sampling consumes the least time as it requires selection of sample size and identification of starting point for this sample that needs to be continued at regular intervals to form a sample.
Steps to form a systematic sample:
A defined structural audience (population) to start working on the sampling aspect.
Figuring out the ideal size of the sample (prefer bigger size to achieve accurate results).
To each and every member of the sample,a number must be assigned.
Calculating the sampling interval (population size/sample size).
A number will be randomly chosen as the starting member (r) of the sample between 1 and (N/n) and this interval will be added to the random number to keep adding members in the sample. r, r+i, r+2i etc. will be the elements of the sample.
Types of Systematic Sampling:
Linear systematic sampling:
A systematic sampling method where samples arenot repeated at the end and ‘n’ units are selected to be a part of a sample having ‘N’ population units. It stops at the end of a population.
Circular systematic sampling:
In circular systematic sampling, a sample starts again from the same point once again after ending, which is similar to linear systematic sampling but with a repetition. For example, if N = 7 and n = 2, k=3.5 named as a, b, c, d, e. There are two probable ways to form sample:
- If we consider k=3, the samples will be – ad, be, ca, db and ec.
- If we consider k=4, the samples will be – ae, ba, cb, dc and ed.
| Linear Systematic Sampling | Circular Systematic Sampling |
| samples = k (sampling interval) | samples = N (total population) |
| The starting and ending points of this sample are distinct. | Repeats from the start point once the entire population is considered. |
| Arranged in a linear manner prior to selection. | Arranged in a circular manner. |
Advantages:
Simple and convenient to create, conduct, and analyze samples by the researchers.
Beneficial in case of diverse population because of the even distribution of sample.
Disadvantages:
Difficult when the population size cannot be estimated.
Data becomes skewed if sample is taken from a group which already has a pattern.
Sometimes even a standard arrangement (order/pattern) may not be obvious or visible, resulting in sampling bias.