3.1 Sampling Flashcards
Population
The set of things you are interested in
Sample
The subset of the population
Parameter
The number that describes the entire population
Statistic
A number taken from a single sample
Census
Observes or measures every member of a population
It can be a survey/experiment
Adv and Disadv of census
Adv
- give a completely accurate result
Disadv
- time consuming
- expensive
- hard to process large quantity of data
Adv and disadv of sample
Adv
- less time consuming
- less expensive
- fewer people have to respond
- less data to process compared to census
Disadv
- data may not be accurate
- sample may not be large enough to give info about small sub-groups of the population
Sampling unit
Individual units of a population
Sampling frame
This is where sampling units of a population are individually named or numbered to form a list
Different types of sampling
- Simple random sampling
- Systematic sampling
- Stratified sampling
- Opportunity sampling
- Quota sampling
- Cluster sampling
Simple random sampling
Every member of the population is equally likely to be chosen. (A simple random sample of size n is one where every sample of size n has an equal chance of being selected)
Eg
Allocate each member in population a number and then use random numbers to choose a sample of desired size
Systematic sampling
Find a sample of size n from a population of size N by taking one member from the first k members of the population at random and then selecting every kth member after that.
Equation for systematic sampling
K = N/n
Stratified sampling
When you know you want distinct groups to be represented in your sample, split the population into these distinct groups and then sample within each group in proportion to its size.
Equation for stratified sampling
Adv and disadv of simple random sampling
Adv
- free of bias
- easy and cheap to implement for small populations
- each sampling unit has a known and equal chance of selection
Disadv
- not suitable when the population/sample size is large
- a sampling frame is needed
Adv and disadv of systematic sampling
Adv
- simple and quick to use
- suitable for large samples and large populations
Disadv
- a sampling frame is needed
- can introduce bias if the sampling frame is not random
Adv and disadv of stratified sampling
Adv
- sample accuracy reflects the population structure
- guarantees proportional representation of groups within population
Disadv
- population must be clearly classified into distinct strata
- selection within each stratum suffers from the same disadvantages as simple random sampling
Quota sampling
When you know you want distinct groups to be represented in your sample, decide how many members of each group you wish to sample in advance and use opportunity sampling until you have a large enough sample for each group.
Opportunity sampling
Take samples from members of the population you have access to until you have a sample of the desired size.
Cluster sampling
Split the population into clusters that you expect to be similar to each other, then take a sample from each of these clusters.
Adv and disadv of quota sampling
Adv
- allows a small sample to still be representative of the pop
- no sampling frame required
- quick and easy and inexpensive
- allows for easy comparison between diff groups within a population
Disadvantage
- non-random sampling can introduce bias
- pop must be divided into groups, which can be costly/inaccurate
- non-responses are not recorded as such
Adv and disadv of opportunity sampling
Adv
- easy to carry out
- inexpensive
Disadv
- unlikely to provide a representative sample
- highlight dependent on individual researcher
Quantitative variable/data
Variables or data associated with numerical observations
Qualitative variable/data
Variables or data associated with non-numerical observations
Continuous variable/data
A variable/data that can take any value in a given range
Eg height
Discrete variable/data
Variable/data that can only take specific values in a given range
Eg feet size, blood group
