Statistics- Data Collection (1) Flashcards
Population
Whole set of items that are of interest
Census
Observes/measures each member of a population
Sample
Selection of observations taken from a subset of the population, used to find information about the whole population
Census Advantages
Completely accurate
Census Disadvantages
- Time consuming and expensive
- Cannot be used if the testing process destroys the item
- Hard (or impossible) to process large quantities of data
Sample Advantages
- Less time consuming and less expensive than a census
- Fewer responses needed
- Less data to process
Sample Disadvantages
- Data may not be accurate
- Sample may not be large enough to reflect all subsets
Sampling units
Individual units of a population
Sampling frame
List of individually numbered or named sampling units
3 main random sampling methods
- Simple random
- Systematic
- Stratified
Simple random sampling
Sample is chosen randomly using a random number generator
-requires a sampling frame to be set up
Systematic sampling
Every nth member of the population is chosen from an ordered list where
- n=population size/sample size
- first element should be a random number between 1 and n
Stratified sampling
Population is divided into mutually exclusive strata and a random sample is taken from each
-proportion of each strata should be the same
Stratified sampling formula
Number sampled in a stratum= (number in stratum/ number in population)*overall sample size
Simple random sampling ADV
- Free of bias
- Easy and cheap to implement for small populations and samples
- Each sampling unit has a knows and equal chance of selection
Simple random sampling DISADV
- Not suitable when there is a large population or sample size
- A sampling frame is needed
Systematic sampling ADV
- Simple and quick
- Suitable for large samples and populations
Systematic sampling DISADV
- A sampling frame is needed
- Can introduce bias if the sampling frame is not random (two people together are unlikely to be selected)
Stratified sampling ADV
- Accurately reflects population structure
- Guarantees proportional representation of groups in the population
Stratified sampling DISADV
- Population must be clearly classified into distinct strata
- Selection within each stratum suffers the same disadvantages as simple random sampling
2 main non-random sampling methods
- Quota
- Opportunity
Quota Sampling
An interviewer or researcher selects a sample that reflects the characteristics of the whole population
Opportunity Sampling
Sampling the people who are available whilst the study is carried out and fit criteria
Quota sampling ADV
- Allows a small sample to represent the whole population
- No sampling frame needed
- Quick, easy, inexpensive
- Allows for easy comparison between different groups
Quota sampling DISADV
- Non random= bias
- Population must be divided into groups
- Increasing scope of study increases the number of groups, take time and money
- Non-responses aren’t recorded as such
Opportunity sampling ADV
- Easy to carry out
- Inexpensive
Opportunity sampling DISADV
- Unlikely to provide a representative sample
- Dependent on individual researcher
Quantitative variable
Data associated with numerical observations
Qualitative variable
Data associated with non-numerical observations
Continuous variable
A variable that can take any value in a given range
Discrete variable
A variable that can only take specific values in a given range
Class
The groups data is presented in in a grouped frequency table
Class boundaries
Max and min values in each class
Midpoint
Average of the class boundaries
Class width
Difference between upper and lower boundaries
