I think that the answer would be 2 if I am right 
        
                    
             
        
        
        
Answer:
Type I: 1.9%, Type II: 1.6%
Step-by-step explanation:
given null hypothesis
H0=the individual has not taken steroids.
type 1 error-falsely rejecting the null hypothesis
⇒   actually the null hypothesis is true⇒the individual has not taken steroids.
  but we rejected it ⇒our prediction is the individual has taken steroids.
typr II error- not rejecting null hypothesis when it has to be rejected
⇒actually null hypothesis is false ⇒the individual has taken steroids.
but we didnt reject⇒the individual has not taken steroids.
let us denote 
the individual has taken steroids by 1
the individual has not  taken steroids.by 0
                             predicted
                                1       0
    actual          1    98.4%  1.6%
                         0   1.9%   98.1%
so for type 1 error  
  actual-0
predicted-1
therefore from above table we can see that probability of Type I error is 1.9%=0.019
so for type II error 
    actual-1
predicted-0
therefore from above table we can see that probability of Type I error is 1.6%=0.016
 
        
             
        
        
        
To be exact it would be 27.8 but the nearest would be 33 degrees so the answer is A
        
             
        
        
        
Question: 

There are two methods of doing this. One is via long division. It is long, and hard to type in a meaningful way, so I will not include that method. The other, which I often employ for dividing by small amounts such as 4, is to divide it in half 2 times. This is possible because 4 = 2 times 2. You now have the fractions 

Therefore the solution is 90.