7:32 PM
Cramer's rule says that to solve Ax=b (A an nxn matrix, x,b n,1 column vectors) you compute the determinants of A (call that D) and of the matrices you get by replacing one column of A with b (call that D_i when you replace the i'th column). Then x_i = D_i/D.
So for n=3 you need to be able to compute determinants of 3x3 matrices.
I don't know what definition of determinant you've been given, but for 2x2 and 3x3 matrices it turns out that a nice easy-to-remember procedure works (but BE CAREFUL it doesn't work for n>3). Look at all the diagonals of the matrix, including ones that "wrap around". For each of them, multiply together all the elements along that diagonal. Then add up the ones for diagonals running NW-to-SE and subtract the ones for diagonals running SW-to-NE.
So if your matrix is (a b c; d e f; g h i) then you have the obvious NW-to-SE diagonal aei. But you also have (starting at b) bfg, which wraps around from the second to the third row, and (starting at c) cdh, which wraps around from the first to the second row. Those all have positive sign.
In the other direction we have ceg which doesn't have to wrap, but also bdi and afh.
So the determinant is (aei+bfg+cdh) - (ceg+bdi+afh).
So to apply Cramer's rule, you just need to do that four times, once with your original matrix A and once for each of the three modified ones.
Again, that method of calculating the determinant works for 2x2 and 3x3 matrices but NOT for larger ones. (Nor for smaller ones: it would make the determinant of any 1x1 matrix zero.) The thing that's true in general is that to calculate the determinant of a matrix you look at all ways of picking one element from each row, and for each of those you multiply all the elements together and multiply by +1 or -1 depending on "the sign of the permutation" (details available if wanted ...
... but never mind for now) and all all those up, and for 2x2 and 3x3 matrices the only ways to pick one element from each row are ones that just go along a diagonal in one of the two "45-degree" directions, but that's very untrue for larger matrices.