Sampling: 

Definitions:

Population = a complete set of items or individuals

Samples = a group of items forming a subset or a population

Sampling units = individual members of a population

Sampling frame = list containing sampling units

A census = a survey of all the items or individuals in the population this has the advantage that all the items in the population are included so questions can be answered accurately and without bias, but it can be time consuming and expensive to carry out

Sampling:

advantages:

• cheap and quick
• Not all of the data is needed
• Less data to process than in a census

disadvantages:

• subject to natural variation
• May be bias in the sample

simple random sampling:

A simple random sample of size n is one where every simple of size n has a equal chance of being chosen

To carry out a simple random sample, you need a sampling frame, usually a list of people or things. Each person or thing is allocated a unique number and a selections of these numbers is chosen at random

advantages:

• free of bias
• Easy and cheap
• Each unit has a known and equal chance of selections

disadvantages:

• not suitable with a large sample size
• Sampling frame is needed

systematic sampling:

In systematic sampling, the required elements are chosen at regular intervals from a ordered list

advantages:

• simple and quick to use
• Suitable for large samples and populations

disadvantages:

• a sampling frame is needed
• It can introduce bias if the sampling frame isn’t random

stratified sampling:

In stratified sampling, the population is divided into mutually exclusive strata (e.g. males and females or age groups) and a random sample is taken from each, the number taken must be in proportion

advantages:

• sample accurately reflects the population structure
• Guarantees proportional representation of groups

disadvantages:

• population must be clearly classified into strata
• Selection within each stratum suffered from it not being able to be used for large populations and a sampling frame is needed

Quota sampling:

In quota sampling, a researcher selects a sample that reflects the characteristics of the whole population. The population is divided into groups according to a given characteristics and the size of each group determines the proportion of the sample that should have that characteristic.

Advantages:

• allows a small sample to still be representative
• No sampling frame needed
• Quick, easy and inexpensive
• Easy comparison

disadvantages:

• can introduce bias
• Dividing into groups can be expensive and inaccurate
• Takes time and expense
• Non-responses are not recorded as such

Opportunity sampling:

Also called convenience sampling consists of taking the sample from the people available at the time the study is carried out and who fit the criteria you’re looking for, e.g. meeting someone outside a supermarket

advantages:

• easy to carry out
• Inexpensive

disadvantages:

• Doesn’t provide a representative sample
• Highly dependant of individual researcher