BIOL 243 Lecture Notes - Lecture 2: Sampling Error, Cohort Study, Confounding

• School: Queen's University
• Department: Biology
• Course: BIOL 243
• Professor: Christopher G Eckert

Document Summary

Select a group of units that are a good representation for the population. Can be broken down to 4 components: units must have a known and non-zero probability of being included in your sample, unbiased, should not just be one sample, must include the true population. Independent, when selecting one unit to be in your sample, should not influence other units being selected: each possible sample has equal chance of being selected. A natural variation from one random sample to another. Main goal is to characterize an existing population. Draw backs are correlative, but not causal: correlation shows the trends, but causation is rarely definable with this method. Confounding variables, are variables we haven"t observed, but are likely driving relations to those we have observed. Look at all who have a disease. Look for commonalities for those that have a disease that are not common in those who are not diseased. Can be done for a snap shot in time.