Statistics 1 Flashcards
Population
The whole set of items that are of interest
Raw data
Unprocessed information
Census (purpose)
Observe or measure every member of a population
Sample
A selection of observations taken from a subset of the population, used to find out information about the population as a whole
Census (adv vs dis)
Advantages:
- should give a completely accurate result
Disadvantages:
- Time consuming
- Expensive
- Can’t be used when testing process destroys the item
- Hard to process large quantities of data
Sample (adv vs dis)
Advantages:
- Less time consuming and expensive
- Fewer people have to respond
- Less data to process
Disadvantages:
- Data may not be as accurate
- Sample may not be large enough to give information about small sub-groups of the population
Size of sample -> validity of conclusions
• Generally, the larger the sample, the more accurate it is, but you will need greater resources
• If population is very varied, larger sample needed than if the population were uniform
• Different samples can lead to different conclusions due to the natural variation in a population
Sampling units
Individual members of population
Random sampling
Every member of the population has an equal chance of being selected
It’s representative of the population
Helps remove bias from a sample
Simple random sampling
A SRS of size n is one where every sample of size n has an equal chance of being selected
Simple Random Sampling (adv vs dis)
Advantages:
- Free of bias
- Easy and cheap to implement for small samples and populations
- Each sampling unit has a known and equal chance of selection
Disadvantages:
- Not suitable for large population/sample sizes (time consuming/ disruptive/ expensive)
- A sampling frame is needed
Systematic sampling
The required elements are chosen at regular intervals from an ordered list
Systematic Sampling (adv vs dis)
Advantages:
- Simple and quick to use
- Suitable for large samples and populations
Disadvantages:
- Sampling frame needed
- Can introduce bias if sampling frame is not random
Stratified sampling
The population is divided into mutually exclusive strata (of the same size) and a random sample is taken from each
Numbered sampled in a stratum
Number in stratum
—————————— x overall sample size
Number in population
Stratified sampling (adv vs dis)
Advantages:
- Sample accurately reflects population structure
- Guarantees proportional representation of groups within a population
Disadvantages:
- Population must be clearly classified into distinct strata
Selection within each stratum
- Sampling frame needed
- Consuming, disruptive, expensive for large sizes
