Unit 1- Statistical Sampling Flashcards
Population
The whole set of items that are of interest
Census
Observes or measures every member of a population
Sample
Selection of observations taken from a subset of the population which is used to find out information about the population as a whole
Sampling units
Individual units of a population (often individually named/numbered)
Sampling frame
A list of sampling units
Advantage(s) of a census
Should give a completely accurate result
Disadvantage(s) of a census
- Time-consuming and expensive
- Can’t be used when testing destroys the item
- Hard to process if a large quantity
Advantages(s) of a sample
- Less time-consuming and expensive
- Fewer people are needed
- Less data to process
Disadvantage(s) of a sample
- Data may not be as accurate
- Not enough sample to inform about small sub-groups of the population
Random sampling
Every member of the population has an equal chance of being selected, so the sample would be representative of the population
Three methods of random sampling
Simple random sampling, systematic sampling and stratified sampling
Simple random sampling
Allocate each person or thing a unique number and then randomly generate using a random number table or lottery sampling
Lottery sampling
The members of the sampling frame could be written on tickets and placed into a ‘hat’
Systematic sampling
The required elements are chosen at random intervals from an ordered list
Stratified sampling
The population is divided into mutually exclusive strata and a random sample is taken from each
The number sampled in a stratum =
(number of stratum / number in population) * overall sample size
Advantage(s) of random sampling
- Free of bias
- Easy and cheap for small populations/samples
- Each sampling unit has a known equal chance
Disadvantage(s) of random sampling
- Not suitable when the population or sample size is large
- A sampling frame is needed
Advantage(s) of systematic sampling
- Simple and quick to use
- Suitable for large samples/populations
Disadvantage(s) of systematic sampling
- A sampling frame is needed
- Can introduce bias if the sampling frame is random
Advantage(s) of stratified sampling
- Sample accurately reflects the population structure
- Guarantees proportional presentation of groups in a population
Disadvantage(s) of stratified sampling
- Population must be clearly classified into distinct strata
- A sampling frame is needed
- Not suitable when the population/sample size is to large
Two methods of non-random sampling
Quota sampling and opportunity sampling
Quota sampling
An interview selects a sample that reflects the characteristics of a wide population and allocates them into an appropriate quota
Opportunity sampling
Taking the sample from people who are available at the time the study is carried out and who fit the required criteria
Advantage(s) of quota sampling
- Allows a small sample to still be representative
- No sampling frame needed
- Quick, easy and cheap
- Easy to compare between different groups
Disadvantage(s) of quota sampling
- Can introduce bias
- Population must be divided into groups which can be costly or inaccurate
- Increasing scope of study increases number of groups, increasing time and expense
- Non-responses aren’t recorded as such
Advantage(s) of opportunity sampling
- Easy to carry out
- Inexpensive
Disadvantage(s) of opportunity sampling
- Unlikely to be representative
- Dependant on each researcher
Quantitative data/variables
Associated with numerical observations
Qualitative data/variables
Associated with non-numerical observations
Continuous variable
Can take any value in a given range
Discrete variable
Can only take specific values in a given range
Class boundaries in a group frequency table
The maximum and minimum values in each class
Midpoint in a group frequency table
The average of the class boundaries
Class width in a group frequency table
The range of the class boundaries
