Types of Sampling (Leaving Cert Mathematics): Revision Notes

Types of Sampling

Sampling Techniques

Simple Random Sampling

• This method ensures that each member of the population has an equal chance of being chosen.
• A possible method for choosing such a sample:
  1. Assign each member of the population an integer $1, 2, \ldots, n$, where $n$ is the size of the population.
  2. Determine the sample size $s$.
  3. Using a random number generator, generate integers, and if an integer chosen corresponds to a number assigned to a member of the population, choose them to be part of the sample. Ignore repeated numbers and numbers out of range.
  4. Stop when we have a sample of $s$ objects.

Stratified Sampling

• This is a sampling technique in which each subcategory of the population is proportionally represented within the sample.

• Once the size of subcategories is chosen for the sample, use simple random sampling on each subcategory.

Systematic Sampling

• This involves coming up with a rule to apply to the population to generate your sample.
  • Example: Choosing every $10$th person from a list of the entire population. All of the above sampling methods assume that participants are willing. This is rarely the case. In such circumstances, where willing participants are scarce, the following methods could be used:

Opportunity Sampling

• Ask the first people you see until you have enough data.

Quota Sampling

• Have an idea of how many of each subcategory of the population are to be surveyed (e.g., like in stratified sampling), then use opportunity sampling to fill these quotas.

Cluster Sampling

• Choose a cluster of people from a population, then ask them all.