Systematic Sampling
Definition:
Systematic sampling is a statistical method for selecting a fixed number of items from a population. It is often used in market research and opinion polls.
For example, if one wanted to select every 10th member of a population, they would use systematic sampling. This type of sampling is often used when it is difficult or impossible to obtain a complete list of the members of the population (e.g., when studying street children). It is also used when time or other resources are limited.
Types of Systematic Sampling
There are three types of Systematic Sampling
- Systematic random sampling
- Linear systematic sampling
- Circular systematic sampling
Systematic random sampling
Systematic random sampling is a method of selecting a sample from a population in which each member of the population has an equal chance of being selected. This type of sampling is often used when it is not possible or practical to obtain a complete list of all members of the population.
To select a systematic random sample, the researcher first decides on the size of the sample (n) and the interval (i). The interval is usually set at 1, but can be any number as long as all members of the population have an equal chance of being selected.
The researcher then begins by selecting a random starting point from within the population. To do this, they may use a table of random numbers or some other method. Once the starting point has been selected, every nth member of the population is chosen until the required sample size is reached.
Linear systematic sampling
Linear systematic sampling is a statistical method used to select a fixed number of samples from a larger population. This selection process begins by randomly choosing the first unit from the population, then selecting every Nth unit thereafter. This type of sampling is often used when studying items that are arranged in a linear fashion, such as books on a shelf or people in line.
Circular systematic sampling
Circular systematic sampling is a sampling technique in which units are selected from a population using a systematic approach. The population is first divided into strata, and then a random start point is selected within each stratum. The unit at the start point is selected, and then every kth unit is selected until the required sample size is reached. This type of sampling technique can be used when the population units are arranged in a circular fashion, such as when sampling from a circular frame.
How to conduct Systematic Sampling
There are Some steps that must be followed in order to conduct systematic sampling correctly.
- First, the researcher must determine the desired sample size.
- Second, the researcher must identify the population from which the sample will be drawn.
- Third, the researcher must select a starting point within the population and then select every Nth member of the population until the desired sample size is reached.
If done correctly, systematic sampling can be an effective way to obtain a representative sample from a population. However, there are some potential drawbacks to this method. One is that if the starting point is not selected randomly, it could introduce bias into the results.
When to use Systematic Sampling
This method is often used when conducting surveys or other research studies. There are several factors to consider when deciding whether or not to use systematic sampling in your research.
- You must have a complete list of the population you wish to study. This list can be difficult to obtain, which can make systematic sampling impractical.
- The list must be in random order; if it is not, the results of your study could be biased.
- You must determine the interval at which you will select subjects from the list. This interval should be based on the size of the population and the desired precision of your results.
Example of Systematic Sampling
An example of systematic sampling would be if you were to choose every 10th person from a line of 100 people. In this instance, your sample size would be 10 and your sampling interval would be 10. This type of sampling is often used when studying a population that is difficult to access, such as a group of school children or patients in a hospital. It is also used when the population is too large to study in its entirety, such as all the residents of a city.
Importance of Systematic Sampling
Systematic sampling is important because it minimizes bias and ensures that the sample is representative of the population.
For example, let’s say you want to study the television watching habits of American adults. You could use a systematic sampling method to select a sample of adults from all 50 states. This would ensure that your sample was representative of the entire population, and not just one region or group of people.
Systematic sampling is also important because it is easy to replicate and verify. This makes it an ideal choice for research that will be replicated or extended in the future.
Advantages of Systematic Sampling
There are some advantages of systematic sampling:
- It is easy to understand and implement.
- Systematic sampling eliminates the need for a complete enumeration of the population, which can save time and resources.
- It can be used to select a representative sample when the population is too large or difficult to enumerate.
- When done correctly, can provide reliable results that can be used to make inferences about a population.
Disadvantages of Systematic Sampling
There are some disadvantages of systematic sampling.
- If the sampling interval is not properly chosen, it can result in a biased sample.
- Systematic sampling can be less effective than other methods if the population is not homogeneous.
- It can be difficult to implement if the population is large or spread out over a wide area.
