SAMPLING PRELIM Flashcards
The process to SELECTING THE SAMPLE. When you conduct research about a group of people, it’s rarely possible to collect data from every person in that group.
Sampling
For the researcher to CAREFULLY DECIDE how you will select a sample that is REPRESENTATIVE OF THE GROUP AS A WHOLE.
sampling method
There are TWO PRIMARY TYPES OF SAMPLING METHODS that you can use in your research
- The population
- The sample
There are TWO PRIMARY TYPES OF SAMPLING METHODS that you can use in your research
- The population
- The sample
is the ENTIRE GROUP that you want to draw conclusions about
The population
is the SPECIFIC GROUP OF INDIVIDUALS that you will collect data from. This should be a representative of the population
The sample
is the SPECIFIC GROUP OF INDIVIDUALS that you will collect data from. This should be a representative of the population
The sample
SLOVIN’S FORMULA FOR SAMPLE SIZE
n = N / (1+Ne2)
n = sample
N = Population
1 = Constant
e = margin of error (e = 0.05 (5%) )
SLOVIN’S FORMULA FOR SAMPLE SIZE
n = N / (1+Ne2)
n = sample
N = Population
1 = Constant
e = margin of error (e = 0.05 (5%) )
involves RANDOM SELECTION (PURE CHANCE), allowing you to make strong statistical inferences about the WHOLE GROUP.
Probability sampling
involves RANDOM SELECTION (PURE CHANCE), allowing you to make strong statistical inferences about the WHOLE GROUP.
Probability sampling
involves NON-RANDOM SELECTION based on convenience or other criteria,
allowing you to EASILY COLLECT DATA.
Non-probability sampling
means that EVERY MEMBER OF THE POPULATION a chance of being selected.
Probablity Sampling
means that EVERY MEMBER OF THE POPULATION a chance of being selected.
Probablity Sampling
EVERY MEMBER OF POPULATION has an EQUAL CHANCE OF BEING. Your
sampling frame should include the whole population.
Simple random sampling
EVERY MEMBER OF POPULATION has an EQUAL CHANCE OF BEING. Your
sampling frame should include the whole population.
Simple random sampling
similar to simple random sampling, but it is USUALLY SLIGHTLY EASIER TO CONDUCT. Every member of the population is LISTED WITH A NUMBER, but instead of randomly generating numbers, individuals are chosen at regular intervals.
Systematic sampling
involves DIVIDING THE POPULATION INTO SUBPOPULATIONS that may differ in important ways. It allows you draw more precise conclusions by ensuring that EVERY SUBGROUP is properly represented in
the sample.
Stratified sampling
involves DIVIDING THE POPULATION INTO SUBPOPULATIONS that may differ in important ways. It allows you draw more precise conclusions by ensuring that EVERY SUBGROUP is properly represented in
the sample.
Stratified sampling
also involves dividing the population into subgroups, but each subgroup SHOULD HAVE SIMILAR CHARACTERISTICS TO THE WHOLE SAMPLE. Instead of sampling individuals from each subgroup, you randomly select entire subgroups.
Cluster sampling
INDIVIDUALS ARE SELECTED BASED ON NON-RANDOM CRITERIA, and not every individual has a chance of being included.
Non-probability sampling
simply includes the individuals who happen to be MOST ACCESSIBLE TO THE RESEARCHER. It can be RISK FOR BOTH SAMPLING BIAS and selection bias.
convenience sample
simply includes the individuals who happen to be MOST ACCESSIBLE TO THE RESEARCHER. It can be RISK FOR BOTH SAMPLING BIAS and selection bias.
convenience sample
mainly based on EASE OF ACCESS. Instead
of the researcher choosing participants and directly contacting them, PEOPLE VOLUNTEER THEMSELVES (e.g. by responding to a public online survey).
Voluntary response sampling
