HSS 3101 Lecture Notes - Lecture 6: Bernoulli Sampling, Systematic Sampling, Uptodate

• School: University of Ottawa
• Department: Health Sciences
• Course: HSS 3101
• Professor: Jason Steffener

Document Summary

A spoonful of soup tells you what kind of soup it is. Sampling: means to select subset of units from a population to collect information to draw inferences about a whole population. Two types of sampling are: non-probability sampling: selecting individuals from a population using a subjective (ie. non-random) method, probability sampling: relies on probability to describe the odds of an individual being selected in a sample, non-probability sampling. Subjective method to select units from a population. Must assume sample represents population in order to make inferences, which is dif cult due to biases (risky assumption) Inclusion probability can"t be calculated due to selection bias so it can"t produce reliable estimates. Used often to generate ideas, as a preliminary step, or as a follow-up step. Unclear whether or not it is possible to generalize the results from the sample of the population (selection can result in large biases) Selection of units based on randomization or chance.