Powerpoint on Sampling Flashcards
What is a sample and why do we use it think time and money
Sampling is the process by which subgroup of participants is selected for study from a larger group of potential participants.
Why sample?
Resources (time, money) and workload
Gives results with known accuracy that can be calculated mathematically
How do we determine our population of interest?
Administrators can tell us
We notice anecdotally or through qualitative research that a particular subgroup of students is experiencing higher risk
We decide to do everyone and go from there
3 factors that influence sample representativeness
Sampling procedure
Sample size
Participation (response)
When might you sample the entire population?
When your population is very small
When you have extensive resources
When you don’t expect a very high response
Give an example on how the sample process goes about
The sampling process comprises several stages: Defining population (N) to be sampled Specifying a sampling method for selecting items or events from the frame Determining the sample size Implementing the sampling plan Control for bias and error Sampling and data collecting Reviewing the sampling process
Describe a sample bias and a Sampling error:
SAMPLING BIAS: It occurs when the individuals selected for a sample overrepresent or underrepresent population attributes that are related to the phenomenon under study. It can be conscious or unconscious.
SAMPLING ERROR: It is the difference between sample averages (called statistics) and population averages (called parameters).
Proability sampling (4) characteristics
non-probability samples (3) tell me each one
Probability (Random) Samples Simple random sample Systematic sample Stratified sample Cluster sample Non-Probability Samples Sample of convenience Snowball sampling Purposive sampling
difference between probability sampling and non probability sampling
Probability sampling Randomization Easy generalization Less sampling error Less variable Better approximation of the population
Non-probability sampling
No randomization
More sampling error
Describe simple sampling random (just think like drawing form a hat)
Is a procedure in which each member of the population has an equal chance of being selected sample, and selection of each subject is independent of selection of other participants
“DRAW” the sample from a cage, or even from hat is difficult with larger population
advantage and disadvantage of the simple sample.
Applicable when population is small, homogeneous & readily available.
A table of random number or lottery system is used to determine which units are to be selected.
If sampling frame large, this method impracticable.
Minority subgroups of interest in population may not be present in sample in sufficient numbers for study.
Systematic Sampling describe
Systematic sampling is process by which the researcher selects every nth person on a list.
Systematic sampling involves a random start and then proceeds with the selection of every nth person from then onwards.
A simple example would be to select every 10th name from the hospital admission list.
Advantages and disadvantage of Systematic sampling
ADVANTAGES:
Sample is easy to select.
Suitable sampling frame can be identified easily.
Sample evenly spread over entire reference population.
DISADVANTAGES:
Sample may be biased if hidden periodicity in population coincides with that of selection.
Difficult to assess precision of estimate from one survey.
Stratified Sampling describe: (like when this certain sample of people must be asian people kind of thing)
It is used:
when certain subgroups must be presented in adequate numbers within the sample.
or
when it is important to preserve the proportions of subgroups in the population within sample.
Advantages of Stratified sampling and disadvantages
All units in the accessible population are identified according to the stratification.
The appropriate number of participants is selected from each stratum.
Participants may be selected from each stratum through simple random sampling or systematic sampling.
More than one stratum may be identified.
It is easy to accomplish if the stratifying characteristics is known for each sampling unit.
Sampling frame of entire population has to be prepared separately for each stratum.
When examining multiple criteria, stratifying variables may be related to some, but not to others, further complicating the design, and potentially reducing the utility of the strata.
In some cases (such as designs with a large number of strata, or those with a specified minimum sample size per group), stratified sampling can potentially require a larger sample than would other methods.
Cluster sampling explain what this means
It is used when an appropriate sampling frame does not exist or when logistical restraints limit the researcher’s ability to travel widely.
There are often several stages to a cluster sampling procedure.
Population divided into clusters of homogeneous units, usually based on geographical contiguity.
Sampling units are groups rather than individuals.
A sample of such clusters is then selected.
All units from the selected clusters are studied.
(Good for large populations)
Adavantages of cluster sampling
Cluster sampling can save time and money compared with simple random sampling because participants are clustered in locations.
It may also be necessitated by administrative constrains.
Why do we use non probability sampling in the PT
mainly cause of lack of funding
describe convince sampling and what it is good for????
It is used for readily available and convenient participants.
The researcher using such a sample cannot scientifically make generalizations about the total population from this sample because it would not be representative enough.
Students in your class, people on the street, friends.
This type of sampling is most useful for pilot testing
