A far, far safer approach is to do the problem using conditional probabilities. Let A = {7 spades to a & b}, B = {3 spades to c}. We can join a & b to get a larger group ab that receives 26 cards. We want the probability that group ab gets 7 spades and 19 non-spades. This is a hypergeometric probability:
[tex]P(A) = h(7|13,39,26) = \frac{C(13,7) C(39,19)}{C(52,26)},[/tex]
where ##C(a,b) =## "a choose b".
Given that event ##A## occurs, that leaves 26 cards, of which 6 are spades and 20 are non-spades. We draw 13 cards, and want the probability of getting 3 spades (and 10 non-spades). This is a hypergeometric probability
[tex]P(B | A) = h(3|6,20,13) = \frac{C(6,3) C(20,10)}{C(26,13)}.[/tex]
Altogether, we have
[tex]\text{Answer} = P(A \cap B) = P(A) \cdot P(B|A) = \frac{C(13,7) C(39,19) C(6,3) C(20,10)}{C(52,26) C(26,13)}.[/tex]
The hypergeometric distribution just "automates" the processes that you (and other respondents) have done herein; rather than having to re-think each problem, I personally prefer to do it once-and-for-all and apply the results over again to new situation (provided, of course, that the scenarios fit the underlying "hypergeomtric" assumptions). Briefly: the hypergeometric distribution refers to the following: (i) we have ##N_1## objects of tkype I and ##N_2## of type II; (ii) we withdraw ##n## objects randomly, without replacement, from the population of ##N = N_1 + N_2## objects. The probability of the sample having ##k## type-I objects in it is
[tex]P\{ k \; \text{type I} \} = h(k|N_1,N_2,n) = \frac{C(N_1,k) C(N_2, n-k)}{C(N,n)}[/tex]
See, eg.,
https://en.wikipedia.org/wiki/Hypergeometric_distribution or
http://mathworld.wolfram.com/HypergeometricDistribution.html or
http://www.math.utah.edu/~lzhang/teaching/3070summer2008/DailyUpdates/jun23/sec3_5.pdf
for more material on the hypergeometric distribution.