S: data collection Flashcards
Population
Whole set of items of interest
Sample
A selection of observations, taken from a subset of a population, intended to represent the whole population
Sampling unit
Individual units of the population
Sampling frame
A list of sampling units of a population, named or numbered individually
Census
Observes/measures every member of the population
Qualitative/categorical data
Associated with non-numerical observations
Quantitative data
Associated with numerical observations
Continuous variable
Can take any value in a given range
Discrete variable
Can only take specific values in a given range
Census pros and cons
Should give a completely accurate result
Time consuming and expensive
Cant be used when the testing process destroys the item
Hard to process large quantities of data
Sample pros and cons
Less time consuming and expensive than a census
Fewer people have to respond
Less data to process
The data may not be as accurate
The sample may not be large enough to give information about small sub-groups of the population
Simple random sampling (definition, pros, cons)
A simple random sample of size n is one where every sample of size n has an equal chance of being selected
Free of bias
Cheap and easy to implement for small populations
Each sampling unit has a known and equal chance of selection
Not suitable when the population size is large
A sampling frame is needed
Systematic sampling (definition, pros, cons)
The required elements are chosen at regular intervals from an ordered list.
Simple and quick
Suitable for large populations
A sampling frame is needed
It can introduce bias if the sampling frame is not random
Stratified sampling (definition, pros, cons)
The population is divided into mutually exclusive strata and random samples are taken from each.
Sample accurately reflects population structure
Guarantees proportional representation of groups within a population
Population must be clearly classified into distinct strata
Not suitable when the population size is large
A sampling frame is needed
Quota sampling (definition, pros, cons)
An interviewer/researcher selects a sample that reflects the characteristics of the whole population
Allows a small sample to still be representative of the population
No sampling frame is required- quick, easy, not expensive
Allows for easy comparison between different groups in a population
Not random- introduces bias
Population has to be divided into groups- costly and inaccurate
The bigger the scope of the study, the higher the number of groups, the higher the expense and time
Non-responses are recorded as such
Opportunity/convenience sampling (definition, pros, cons)
Taking the sample from people who are available at the time of study and who fit the criteria you are looking for.
Easy to carry out and inexpensive
Unlikely to provide a representative sample
Highly dependent on the individual researcher
Assumption for interpolation
The data is evenly distributed within each class.
Simple random sampling method
Have a sampling frame and allocate each thing a unique number
A selection of numbers is chosen at random using a computer to generate random numbers
Systematic sampling method
Order the elements in the population
Choose a suitable interval
1st person chosen at random
Stratified sampling method
Divide population into mutually exclusive strata (eg. males and females)
Take a random sample from each
no. people sampled in stratum = no. in stratum / no. in population x overall sample size
Quota sampling method
Population is divided into groups according to a given characteristic- the size of each group determines the proportion of the sample that should have that characteristic
Interviewer meets people, assesses group and allocates to quota
This continues until all quotas have been filled, if the person refuses to interview or quota is full ignore them and move on
