CLUSTER SAMPLING

• a survey of selected groups within a population

• the entire population is divided into groups (clusters), and a random sample of these clusters are selected

• used when certain groups called “natural groupings” are likely to be representative of the entire population

Example:The city of London wants to find out how effective the nutritious meals are in elementary schools across the city and surrounding counties.

All elementary students in a local school

district

11 different elementary schools in the local school

district

populationgroups

(clusters)

Example:

every student in the 4 selected

elementary schools

4 elementary schools from the l1 possible elementary

schools

obtain a simple random sample sample

Process: DETERMINE whether or not the population contains “natural” groupings that are representative of the entire population.

DIVIDE the population into groups (clusters).

SELECT a random sample from these clusters.

CONDUCT a survey of the random sample.

ANALYZE the data using statistical techniques.

Advantages:

• cheap, quick, and easy

• the researcher is able to use a larger sample size

Disadvantages:• least representative of the

population out of all the types of probability samples

• high sampling error caused by limited clusters