Definition of Systematic Sampling

Systematic Sampling is a method of sampling where a researcher selects every nth subject or element from a population to be included in the sample. Here, the population is divided into equal-sized intervals, and the researcher randomly selects the first element from the first interval, and subsequently includes every nth element in the sample until the desired sample size is reached.

Advantages of Systematic Sampling

• Efficiency: Systematic sampling is a time-saving method as it requires fewer resources and effort compared to other types of sampling techniques.
• Representative: When the population exhibits a specific order or pattern, systematic sampling is likely to produce a representative sample that accurately reflects the characteristics of the population.
• Easy Implementation: This method is relatively easy to implement as it does not require elaborate randomization procedures, making it suitable for large-scale surveys.

Disadvantages of Systematic Sampling

• Potential Bias: If there is an underlying order or pattern in the population that aligns with the sampling interval, the sample may not accurately represent the entire population, leading to biased results.
• Missed Elements: Systematic sampling carries the risk of excluding certain elements from the sample if they do not align with the chosen sampling interval, resulting in potential bias.
• Limited Flexibility: Unlike other sampling techniques, systematic sampling does not allow for easy adjustments or modifications once the sampling process has begun.

Examples:

A researcher wants to conduct a study on the quality of tap water in a city consisting of 10,000 households. Instead of surveying every single household, the researcher decides to use systematic sampling. By selecting every 100th household starting from a randomly chosen household, the researcher can obtain a representative sample while saving time and resources.