Sampling Methods

Population

A set of similar items you want to draw a conclusion from

Census

Sampling every member of a population

Sample

A subset of data from a larger population

Statistic

A piece of data or fact obtained from numerical data

Random Sampling

Every Sampling Unit has an equal chance of being selected

How do you carry out Random Sampling

• Number each member of the sampling frame from 1 - N

• Randomly generate X numbers

• Sample each unit that is selected

Pro’s of random sampling

• Bias Free

• Cheap

• Each unit has an equal chance of selection

Cons of random sampling

• Sampling frame needed

• Not suitable for large populations

Systematic Sampling

Elements are chosen at regular intervals in an ordered list

How do you carry out Systematic Sampling?

• Start at a number between 1 and K where K = Population/Sample Size

• Pick every Kth element

Pros of systematic sampling

• Quick to use

• Works on large populations

Cons of systematic sampling

• Sampling frame needed

• Can introduce bias if the sampling frame is not random

Stratified Sampling

Population is divided into groups and random sampling is used on each group

How is stratified sampling carried out?

• Split population into strata

• Sample size / Population size = samples per group

• Randomly sample X amount of people from each group

Pros of Stratified Sampling

• Representative of the entire population

Cons of stratified sampling

• Population must be split into strata

• Sampling Frame Needed

Quota Sampling

The population is divided into groups and then actively choose people to sample

How is quota sampling carried out?

• Divide the population into Quota

• Actively sample members of the population and select what quota they belong to

• Repeat until every quota is full

Pros of quota sampling

• No sampling frame needed

• Quick and cheap

Cons of quota sampling

• Bias as not random

• Population must be divided into groups

Opportunity Sampling

People are actively chosen as sampling is carried out

Pros of opportunity sampling

• Cheap and Quick

• No sampling frame needed

Cons of Opportunity Sampling

• Bias

• May not be representative