1. Random sampling: This method involves selecting a random sample of individuals from the population, usually using a random number generator. This helps to ensure that each individual in the population has an equal chance of being selected for the sample.
2. Stratified sampling: This method involves dividing the population into subgroups (strata) based on certain characteristics (such as age, gender, or location) and then selecting a random sample from each subgroup. This helps to ensure that each subgroup is represented in the sample proportionally to their size in the population.
3. Systematic sampling: This method involves selecting every nth individual from a list or queue of the population. The interval (n) is determined based on the total population size and the desired sample size.
4. Cluster sampling: This method involves dividing the population into clusters or groups and then randomly selecting a sample of clusters. All individuals within the selected clusters are then included in the sample. This method is useful when it is not feasible to sample each individual in the population.
5. Convenience sampling: This method involves selecting individuals who are readily available or easy to access. While convenience sampling is quick and cost-effective, it may not be representative of the entire population.
6. Quota sampling: This method involves selecting individuals based on quotas defined by specific characteristics (such as age, gender, or income level). Interviewers are then instructed to fill these quotas by selecting individuals who meet the criteria.
What are the sampling methods used to count abundance of population and their definations
1 answer
1 answer