A simple random sample of this size, drawn from the population of postal workers, provides a manageable subset for research. Each member of the larger postal employee population has an equal chance of being selected for the sample, ensuring representativeness. This method is analogous to drawing names from a hat, where each name has the same probability of being chosen. A sample of this size can be effectively analyzed to infer characteristics of the entire postal workforce.
Selecting a subset through this statistically sound method allows researchers to draw conclusions about the broader population without needing to survey every individual. This approach is cost-effective and time-efficient, particularly when dealing with large populations. Historically, random sampling techniques have been vital for social sciences, market research, and quality control, offering a practical way to gather reliable data and make informed decisions. Its proper implementation is crucial for minimizing bias and maximizing the generalizability of findings to the whole population.