Hey AshleyCS.

A uniform distribution without any extra information is basically a PDF of P(X = x) = 1 for 0 < x < 1 and 0 everywhere else.

You can find the individual density functions using convolution theorems in probability. With regards to the joint distributions, you should consider all pairs of values for x and y for functions u and v.

A few identities that will be useful will include P(U = u, V = v) = P(U=u|V=v)*P(V=v) = P(V=v|U=u)*P(U=u). You can get the conditionals by comparing the different distributions you obtained above.

How much probability have you covered? What topics are you currently studying?