identification of sample and population
population- the entire group a researcher wants to understand or draw conclusions about
sample- the smaller group of people actually selected to participate in the study
random sampling
method of selecting participants so that every member of the population has an equal chance of being chosen
- representative sample
- when a researcher want a representative sample and have access to the full population list
- every member of the population has an equal chance of being selected
- reduces bias, high generalisability, simple to understand
- requires full population list, time consuming, not always practical
identify an example of sample from a population
population- all year 10 students in western australia
sample- 120 year 10 student selected from three randomly chosen schools
convenience sampling
- when researchers need quick, easy access to participants
- participants are selected based on availability and willingness
- fast and inexpensive, easy to conduct, common in early stage research
- high bias risk, low representative, weak generalisability
snowballing sampling
- when studying hard to reach or hidden populations
- existing participants recruit future participants from their social networks
- useful for rare or hidden populations, cost effective, easy to implement
- high risk of bias, low generalisability, sample may be very similar
stratifed sampling
- when the population contains identifiable subgroups and researchers want proportional representation
- population is divide into strata- participants are randomly selected in proportion to from each subgroup their size
- highly representative, ensures key subgroups are included, reduces sampling error
- requires detailed population info
- more complex and time consuming
- hard to use with many small subgroups
