When you sample, what bias are you inflicting?
Selection bias:
– An online survey about computer use is likely to attract people more interested in technology than in typical
Under coverage bias:
– Sample too few observations from a segment of population
Survivorship bias:
– Observations at the end of the study are a non-random set of those present at the beginning of the investigation
– In finance and economics: the tendency for failed companies to be excluded from performance studies because they no longer exist
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How do you control for biases?

• Choose a representative sample, preferably by a random method
• Choose an adequate size of sample
• Identify all confounding factors if possible
• Identify sources of bias and include them as additional predictors in statistical analyses
• Use randomization: by randomly recruiting or assigning subjects in a study, all our experimental groups have an equal chance of being influenced by the same bias

Notes:
– Randomization: in randomized control trials, research participants are assigned by chance, rather than by choice to either the experimental group or the control group.
– Random sampling: obtaining data that is representative of the population of interest
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