In hypothesis testing we set alpha, the significance level, which limits the likelihood of making a Type 1 error if the null hypothesis were true. When does a type 2 error occur? Give a real world example of a decision and explain what the null hypothesis, alternative hypothesis, type 1 and type 2 errors would be - which would be worse in this case: making a type 1 error or making a type 2 error?

Could you use the example: Individuals who receive the flu vaccine are less likely to become ill during flu season.