you will need Bayes theorem.
what i usually do for conditional probability is make a chart.
+--------+------+-------+ | | pass | !pass | +--------+------+-------+ | party | .5 | .5 | | !party | .99 | .01 | +--------+------+-------+
now you can look across the row to see the probability you need. for example. bayes theorem states:
for some event space ${A_i}$,
$ P(A_i|B) = \frac{P(B|A_j)P(A_i)}{\sum\limits_{j}{P(B|A_j)P(A_j)}} $ with $ P(B) = \sum\limits_{j}P(B|A_j)P(A_j) $
let's let:
$ A_1 = $ probability of studying
$A_2 = $ probability of partying
$ B_1 $ = probability of passing
(and) for the sake of completion, $B_2$ = probability of not passing
so to find the probability of partying and still passing we use :
$ P(A_2|B_1) = \frac{P(B_1|A_2)P(A_2)}{P(B_1|A_1)P(A_1)+P(B_1|A_2)P(A_2)}$
(to use the table for $P(B_1|A_1)$ or the probability of passing given studying, simply look up the probability of him studying (in this case !partying) and look up the probabilty of him passing which is .99)
as everyone has already stated, the answer is in fact .3556