In hypothesis testing, relaxing the significance level increases the risk of Type I errors (false positives). A significance level of 0.10 means there is a 10% chance of incorrectly rejecting the null hypothesis. This can lead to more findings being deemed significant due to random chance.

a) What is a Type 2 error and why is it important?

b) What is the impact of relaxing the traditional significance levels from 0.05 to 0.10 in exploratory research on Type 2 error?

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