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Selection Bias - Data was gathered from a biased sample of the population. This is the problem with surveying cat owners to find out which animal is most loved!
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Bias in the Study Design - Data was gathered using a “loaded” question like “Since annual vet care comes to about $300 for dogs and only about half of that for cats, would you say that owning a cat is less of a burden than owning a dog?” This could easily lead to a misrepresentation of people’s true opinions.
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Poor Choice of Summary Data - Even if the selection is unbiased, sometimes outliers are so extreme that they make the mean completely useless at best - and misleading at worst.
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Confounding Variables - A study might find that cat owners are more likely to use public transportation than dog owners. But it’s not that owning a cat means you drive less: people who live in big cities are more likely to use public transportation, and also more likely to own cats. More examples of confounding variables can be found in the correlations lesson: Correlation Does Not Imply Causation!.
These materials were developed partly through support of the National Science Foundation, (awards 1042210, 1535276, 1648684, 1738598, 2031479, and 1501927). 
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