Which sampling method is typically more complex and time-consuming?

Random sampling is considered more complex and time-consuming compared to other sampling methods because it involves selecting a sample in such a way that every possible sample of a specified size has an equal chance of being chosen from the population. This process often requires a comprehensive understanding of the entire population before sampling can begin, making it necessary to maintain strict randomness, which can be difficult to achieve in practice.

In contrast, interval sampling (where samples are taken at regular intervals), systematic sampling (where samples are taken according to a fixed, predetermined rule), and stratified sampling (where the population is divided into subgroups and samples are taken from each) often have clearer procedures and criteria for selection. These methods allow for more straightforward implementations since they can rely on mathematical or defined frameworks, reducing complexity and the time required to ensure that the samples are representative.