4.Sampling
4.1 Non-probability Sampling
4.2 Probability Sampling
4.3 Choosing Non-probability vs. Probability Sampling
4.4 Sample Size
The world’s most famous newspaper error
President Harry Truman against Thomas Dewey
Chicago Tribute prepared an incorrect headline without first getting accurate information
Reason?
- bias
- inaccurate opinion polls
Sampling
Population – the group of people we wish to understand. Populations are often segmented by demographic or psychographic features (age, gender, interests, lifestyles, etc.)
Sample – a subset of population that represents the whole group
Respondents – people who answer
- Most research cannot test everyone. Instead a sample of the whole population is selected and tested.
- If this is done well, the results can be applied to the whole population.
- This selection and testing of a sample is called sampling.
- If a sample is poorly chosen, all the data may be useless.
Sampling: Two General Methods
1. Non-probability Sampling:
This relies on personal judgement of the researcher (often on people available, e.g., people passing in the street or walking through a mall).
This may yield good estimates of population characteristics, however, doesn’t allow for objective evaluation of the precision of sample results. That is, the results are not projectable to the population.
2. Non-probability Sampling:
Here, sampling units are selected by chance, i.e., randomly.
This random techniques ness allows applying statistical to determine the precision of the sample estimates and their confidence intervals. The results are generalizable and projectable to the population from which the sample is drawn.
