Project Maths: Strand 1 - Probability and Statistics
Statistics - Sample Types – 5 types
Sample Types – 5 types
SIMPLE RANDOM SAMPLE: A sample of size n is called a simple random sample
if every possible sample of size n has an equal chance of being selected
(each member of the population has an equal chance of being selected.
STRATIFIED SAMPLING: With stratified sampling, the population is divided
into groups, based on some characteristic. Then, within each group, a
probability sample (often a simple random sample) is selected. In
stratified sampling, the groups are called strata.
As a example, suppose we conduct a national survey. We might divide the
population into groups or strata, based on geography - north, east, south,
and west. Then, within each stratum, we would randomly select survey
respondents the number from each stratum would be proportional to the total
number in the stratum.
CLUSTER SAMPLING: With cluster sampling, every member of the population is
assigned to one, and only one, group. Each group is called a cluster. A
sample of clusters is chosen, using a probability method (often simple
random sampling) and all individuals within sampled clusters are
Note the difference between cluster sampling and stratified sampling. With
stratified sampling, the sample includes elements from each stratum. With
cluster sampling, in contrast, the sample includes elements only from
QUOTA SAMPLING: population is divided into groups based on age, gender,
social class etc. The interviewer is then told how many people (the quota)
to interview in each of these groups. Disadvantage is bias (left to
interviewer who to decide on) Advantage no sampling frame.
CONVENIENCE SAMPLING: selecting a group of people because they are easy to
contact. Advantage it is quick and cheap. Disadvantage high likelihood of
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