ADM 2303 Lecture Notes - Lecture 2: Simple Random Sample, Multistage Sampling, Cluster Sampling

• School: University of Ottawa
• Department: Administration
• Course: ADM 2303
• Professor: Jasmin Manseau

Document Summary

Populations and samples: population: is the entire group of individuals or instances about whom we expect to learn, samples: a sample is a representative sub-set of the. Population: random sample: in a random sample each occurrence or outcome is equally likely. Random samples can be: simple random samples (srs, stratified random samples, cluster samples: the clusters or groups must be heterogeneous and different clusters must be similar for randomness. When samples systematically fail to represent a population, it is known as bias. The following methodologies introduce bias: relying on voluntary response, under coverage or under representation of the population, ignoring non-response, suggestive questions leading to response bias. The campaign chairman of a mayoral candidate selects one block from each of the city"s electoral wards. The chairman would like to know what issues are important to the voters. He directs his staff members to go to these various blocks and interview all the residents they can find.