Maths - Statistics - Sampling Methods

3

3

There are … types of random sampling

simple random, systematic, stratified

examples of random sampling

when every member of the population has an equal change of being selected

random sampling is…

2

There are … types of non-random sampling

quota, opportunity

examples of non-random sampling

when a subjective method is used to select members from a population

non-random sampling is…

sampling where every member has an equal chance of being selected

simple random sampling definition

1. number each member of the population

2. use a calculator/random generator to pick X numbers at random

3. select the members that correspond to the numbers drawn out

simple random sampling steps (3)

• free of bias

• easy and cheap for small samples/populations

advantages of simple random sampling

• a sampling frame (a list of everyone in the population) is needed

• ∴ not suitable for larger samples/populations

disadvantages of simple random sampling

sampling where the required members are chosen at regular intervals from an ordered list

systematic sampling definition

1. number the list in an order (of some sort)

2. pick a member of the list at random to start at

3. divide the size of the population by the sample size to find the interval between each member

4. pick each member that are Y interval apart until sample size is full

systematic sampling steps (4)

• simple and quick to use

• suitable for large samples/populations

advantages of systematic sampling

• a sampling frame (a list of every member in the population) is needed

• bias is introduced if the sampling frame is not randomly ordered

disadvantages of systematic sampling

sampling where the population is split into disjointed, representative groups (such as by ethnicity, by age, by gender) in order to allow sampling to be more proportionate

stratified sampling definition

1. find the overall population size

2. split the population into smaller groups

3. divide each group by the total, to find out what proportion of the population the group takes up

4. times that percentage by the sample size to find out how many data values to take from each group

5. use a random number generator to produce the required quantity of random numbers in each category

stratified sampling steps (5)

• the sample accurately reflects the population structure

• there is a proportional representation of any group in the population

advantages of stratified sampling

• the groups must be distinct - if they are not, the method becomes inefficient

• a sampling frame is still needed

• this is not suitable for large samples/populations

disadvantages of stratified sampling

a researcher selects a sample based on who is available at the time of study (e.g. the first 50 people that walk past, the last 20 people in the shop)

opportunity sampling definition

1. the researcher identifies criteria for their participants

2. they then ask anyone who falls into that criteria whether they would be a part of the investigation

opportunity sampling steps

• easy and inexpensive

advantages of opportunity sampling

• unlikely to provide a representative result

• highly dependent on individual researcher and situation

disadvantages of opportunity sampling

sampling when the population is split into groups (like stratified sampling) and members of the population are selected until each quota is filled

quota sampling definition

1. The population is divided into groups according to a given characteristic (e.g. age). The size of each group determines the proportion of the sample that should have that characteristics

2. An interviewer meets people, assess their group and then (after interview) allocate them into the appropriate quota (e.g. 10 participants age 18-22 don't like ice-cream)

3. This continues until all the quotas have been filled - if a person refuses to be interviewed, or the quota which they fit into is full, they are ignored, and the interviewer moves onto the next person

quota sampling steps

• allows a small sample to be representative of the population

• no sampling frame is needed

• quick, easy and inexpensive

advantages of quota sampling

• population must be divided into groups, which can be costly and inaccurate

• non-responses are not recorded, making the data more bias

disadvantages of quota sampling

collects data about all the members of a population

census

used to collect data from a subset of the population

sampling