Researchers routinely choose an alpha level of 0.05 for testing their hypotheses. What are some experiments for which you might want a lower alpha level (e.g., 0.01)? What are some situations in which you might accept a higher level (e.g., 0.1)?
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Think about what a low alpha test means when the results are found to be significant and what a higher alpha test means when the results are found to be significant. Explain when a lower alpha should be used and when it's okay to use a higher alpha. You should not necessarily need to use resources to find examples.

Interesting article on errors, p-values and significance:

http://www.nature.com/news/scientific-method-statistical-errors-1.14700