When the occurrence of one event say A does not affect the occurrence of another event say B, than the two events are said to be independent such that;
[tex]\\ P(A\cap B)=P(A)\times P(B)[/tex]
where, P(A) = probability of occurrence of event A
and P(B) = probability of occurrence of event B
(a).
Now, let event A = Sarah scores more than 175
and event B = Thomas scores more than 175
Thus, P(A)= Probability that Sarah scores more than 175 = 0.4
and P(B)= Probability that Thomas scores more than 175 = 0.2
Since, the scores are independent, thus the probability that both Sarah and Thomas scores more than 175 is,
[tex]\\ P(A\cap B)=P(A)\times P(B)\\ P(A\cap B)= 0.4\times 0.2= 0.08\\[/tex]
Hence, the required probability is 0.08
(b).
When the occurrence of one event say A affects the occurrence of another event say B, than the two events are said to be dependent such that;
[tex]\\ P(A\cap B)=P(A)\times P(B\setminus A)\\[/tex]
Now, let event A = Sarah scores more than 175
and event B = Thomas scores more than 175
Thus, P(A)= Probability that Sarah scores more than 175 = 0.4
P(B)= Probability that Thomas scores more than 175 = 0.2
and P(B|A) = Sarah scores more than Thomas given that Thomas scores more than 175 = 0.3
Thus, the required probability is calculated as follows;
[tex]\\ P(A\cap B)=P(A)\times P(B\setminus A)\\ P(A\cap B)=0.2\times 0.3=0.06[/tex]