Magic of randomness: sampling
Learning objectives
- Know the basic ideas of sampling
- Examine a part of the whole: A sample can give information about the population.
- Randomize to make the sample representative
- Understand the advantages and disadvantages of the following sampling methods
- Simple Random Sample (SRS): every possible group of n individuals has an equal chance of being our sample.
- Stratified samples can reduce sampling variability by identifying homogeneous subgroups and then randomly sampling within each.
- Cluster samples randomly select among heterogeneous subgroups, making our sampling tasks more manageable.
- Multistage samples combine several random sampling methods.
- Identify and avoid causes of bias
- Voluntary response samples are almost always biased and should be avoided and distrusted.
- Convenience samples are likely to be flawed for similar reasons.
- Bad sampling frames can lead to samples that don’t represent the population of interest.
- Undercoverage occurs when individuals from a subgroup of the population are selected less often than they should be.
- Nonresponse bias can arise when sampled individuals will not or cannot respond.
- Response bias arises when respondents’ answers might be affected by external influences, such as question wording or interviewer behavior.
- Use best practices when designing a sample survey to improve the chance that your results will be valid.