Systematic sampling
Systematic sampling is a sampling technique where the items in a population are selected at regular intervals or intervals based on a predetermined pattern. This sampling method is often used in research and surveys when it is not feasible or practical to survey the entire population.
To implement systematic sampling, a random starting point is selected from the population. Then, at regular intervals, every nth item is selected until the desired sample size is achieved. The interval (n) is calculated by dividing the population size by the desired sample size.
For example, if a researcher wants to survey 100 people from a population of 1000, they would select a random number between 1 and 10 as the starting point. Then, they would select every 10th person from the population until they reach 100 survey respondents.
Systematic sampling provides a representative, yet efficient, way to sample from a large population. However, it assumes that the population is randomly ordered, and any underlying patterns in the population can bias the sample. Therefore, it is important to ensure that the population is randomly ordered or apply a random starting point to minimize bias.
Systematic sampling is a method of sampling where the elements of a population are selected in a systematic and predetermined manner. It is a probability sampling technique that aims to obtain a representative sample of the population.
Here are the steps involved in systematic sampling:
1. Define the population: Start by defining the population you want to study. For example, if you are studying the opinions of students in a particular college, the population would be all the students in that college.
2. Determine the sample size: Decide on the number of elements you want to include in your sample. The sample size should be determined based on factors such as the level of precision required and the resources available.
3. Calculate the sampling interval: The sampling interval is determined by dividing the population size by the desired sample size. For example, if the population size is 1000 and you want a sample size of 100, the sampling interval would be 1000/100 = 10.
4. Randomly select the starting point: To introduce randomness into the sampling process, randomly select a number between 1 and the sampling interval (e.g., using a random number generator). This starting point will be the first element selected for your sample.
5. Select the remaining elements: Once you have selected the starting point, proceed to select the remaining elements for your sample by adding the sampling interval to the previous selection. Repeat this process until you have obtained the desired sample size.
6. Collect data from the sample: Once the sample has been determined, collect data from the selected elements. This could involve conducting surveys, interviews, observations, or any other appropriate method for gathering information.
Note: It is important to note that systematic sampling assumes that the elements in the population are ordered in some manner, such as by a list or a sequential numbering system. If the order of the elements is not important or unknown, a different sampling method may be more appropriate.