Systematic Sampling
Systematic sampling is a probability sampling method where researchers select samples based on a systematic approach from a larger population. It’s a simple and straightforward method commonly used when a population is homogeneous and has no specific patterns.
Steps in Systematic Sampling:
- Define the Population: Determine the total number of individuals in the population (N).
- Determine Sample Size: Decide how many individuals you want in your sample (n).
- Calculate the Sampling Interval (k): k=Nnk=nN The result is the interval at which you will select elements from the population.
- Randomly Select the First Item: Randomly select a number between 1 and k. This will be the starting point.
- Select Subsequent Items: Add the interval (k) to the starting point to get the second item, add k again to get the third item, and so forth, until you’ve reached your desired sample size.
Example of Systematic Sampling
Let’s explore systematic sampling in the context of a retail store wanting to survey its customers.
Scenario: SuperShop Mall Customer Survey
SuperShop Mall has recently made some changes to its store layout and product placement. The management wants to gauge customer satisfaction regarding these changes. They decide to use systematic sampling to survey customers over a month.
Objective: Survey 300 customers over a 30-day period.
Steps:
- Determine Population Size (N): Let’s say SuperShop Mall has an average of 3,000 customers visiting every day. Over 30 days, that’s 90,000 customers.
- Determine Sample Size (n): They want to survey 300 customers over the month.
- Calculate the Sampling Interval (k): k=Nn=90,000300=300k=nN=30090,000=300 This means they’ll survey every 300th customer.
- Randomly Select First Item: On the first day, the manager randomly selects a starting point between 1 and 300. Let’s say the number chosen is 50.
- Select Subsequent Customers: The first surveyed customer on day one is the 50th customer. The next is the 350th (50 + 300), then the 650th, 950th, and so on for the entire month.
Outcome:
By the end of the month, SuperShop Mall would have systematically surveyed 300 customers, providing feedback on the store’s changes. This approach ensures that feedback is collected consistently throughout the month and across different times of the day, offering a comprehensive view of customer sentiments.
This example shows how systematic sampling can be applied practically in a retail context to collect feedback over a specified period. The approach ensures a spread-out and systematic collection of data, making it useful for situations where data needs to be gathered over time or across different segments of a population.
