If the power of a statistical test is known to be .7683, then what is the probability of making a Type II error?

If the alpha level for a statistical test is set a .10 level, what is the probability of making a Type I error?

For the scenarios below type in a:

0 - if it is a correct decision,

or

I - for a TYPE I error

2 - for a TYPE II error

1) A drug test comes back positive for a drug addict. (0,1,2)

2) A patient takes a pregnancy test and it comes out negative, but finds out later that she was in fact pregnant. (0,1,2)

3) In a study conducted for college students sleeping habits, it was found that there was evidence that college students aren't getting the recommended amount of sleep (8 hrs), when in fact they are. (0,1,2)