Title: Probability samples
Course: UGQuants (SSPS) > Section: Survey Design

Probability samples

When we are selecting our sample, we generally (although not always) want it to be representative of the population, i.e., the characteristics of our sample should match those of the population (e.g. in terms of race, gender, social class, age). If our sample is not representative of the population, it will be biased. Analysis based on a biased sample cannot be used to generalise findings from the sample to the population unless statistical adjustments, known as weighting, are carried out during analysis. It is generally assumed that a sample is more likely to be representative if it is a probability sample. As noted, a probability sample is selected using random selection with each member of the population having an equal chance of being selected. There are several types of probability samples which we will now consider: simple random sampling, systematic sampling, stratified sampling and cluster sampling.