The interval of a sampling method refers to the distance or gap between selected samples in a population. This is particularly relevant in systematic sampling, where the sample is chosen at regular intervals.
Here's a breakdown:
Understanding Intervals in Sampling Methods
Imagine you have a population of 100 students, and you want to select a sample of 10 students using systematic sampling. To determine the interval, you would divide the population size (100) by the desired sample size (10), resulting in an interval of 10. This means you would select every 10th student from the list.
- Example: If you start with the first student on the list, you would then choose the 11th student, the 21st student, and so on until you have your sample of 10.
Key Points About Intervals
- Equal Spacing: Intervals ensure that each sample point is equally spaced within the population.
- Representative Sample: A well-chosen interval helps ensure that the sample is representative of the entire population.
- Systematic Approach: The interval provides a systematic and objective approach to selecting samples.
Practical Insights
- Large Populations: Intervals are particularly useful in large populations where manually selecting a random sample would be time-consuming and challenging.
- Data Analysis: Intervals can be used to analyze data trends, patterns, and relationships within a population.
