3. Sampling Validity and reliability Flashcards
what is sampling?
finding participants.
why is it important to sample properly?
so that we can make generalizable inferences
population
a group of people about whom one would like to draw some meaningful conclusions
sample
a subset of that population that is actually included in your research study
sample framw
a list of members/elements of a population from which one might obtain a sample
census
a list of all of the people comprising a particular population
what is critical to have when making generalisable inferences about the population on the basis of measurements of your sample?
representative samples
what are representative samples?
select a sample whose typical characteristic are approximately the same as the typical characteristic of the population
sampel statistics
a numeric characteristic of a sample (measured)
population parameter
a numeric characteristic of the population (often not known)
Resposne rate
what proportion of the people responded?
sampling error
the difference between the sample statistic and the population parameter (depends on the sample size)
what is sampling bias
something that we would like to avoid
probability sampling
a way to ensure that your sample is representative of the population (on the characteristics deemed important for the study
what is the basic principle of probability sampling?
a sample will be representative of the population if all members of the population have an equal chance of being selected in the sample
allows the researcher to calculate the relationship between the sample statistic and the population parameter
what are the types of probability sample
simple random sample systematic random samle stratified random sample multistage cluster sampling Multi-stage / multi-phase sampling
simple random sampling
each member has an equal and independent chance of being selected.
you define the population - list all members - assign numbers.
how would you do random sampling>
using a table of random numbers to select. Use a lottery method
use a computer program to randomly select
systematic random sample
every kth person (k=number).
randomly selected the first person then divides the size of the population bu the size of the desired sample, and use this to determine the interval at which sample is selected.
what must you ensure when doing a systemtic random sample?
that the list of elements is not arranged in a way that means systematic sampling could lead to biased sample (e.g. GPA order)
stratified samplign
if you want to make sure the profile of the sample matches the profile of the population on some important characteristic.
Researcher divides the population into sub populations (strata) and randomly samples from the stata
why use stratified sampling
can reduce sampling error by ensuring ratios reflect actual population (e.g., ratio of males to females)
To ensure that small subpopulations rations reflect actual population (e.g. ratio or males and females)
multi-stange cluster samplingg
• Begin with a sample of groupings and then sample individuals
• E.g. Rural sample
o Define rural townships as those with populations
when might you use multi-stage cluster sampling?
• hunger games – different districts, different characteristics,
Multi-stage / multi-phase sampling
- Larger sample obtained first in order to identify members of a sub-sample
- Sub-sample then randomly chosen from for study
- Good (but costly) way to identify not readily identifiable subgroups
advantages of probability sampling?
helps overcome sampling bias
- representativeness
disadvantages with probaility sampling?
It’s all very well selecting people at random, but the fact that you have selected them doesn’t mean that they will take part in your study…
non-probability sampling
Not every member of the population has an eqyal chance of being part of the sample
why use non-probability sampling?
o There are no lists for some populations under study, e.g.
• The homeless
• Certain occupations (e.g., farmers)
• Hidden populations (e.g., people involved in “clandestine” activities)
• Convenience/ resource restrictions
convenience samples
• A sample of available participants, e.g.,
o students enrolled in a particular course
o People passing a particular location
advantages of convenience samples
easy cheap
disadvantages of convenience samples
no control over representativeness
snowball sampling
Involves collecting data with members of the population that can be located and then asks those members to provide information/contacts for other members of the population
Used mainly for hard to study populations, e.g.,
o Gay men
o Homeless young people
o Illegal immigrants
Quota sampling
- Non-probability sampling equivalent of a stratified random sample
- Want to reflect relative proportions of a population
- But you don’t/aren’t able to sample randomly from each strata as you do in stratified random samples