(please refer to attached image)

The question appears to be simple enough, but i have two queries

A) does E[X1 X2] mean the same as E[X1 | X2]

B) If not/so, how exactly do I go about computing this. I've seen a few formulas in my lectures notes for computing conditional expectations for discrete random variables,

however I find it difficult to understand and apply the notation/procedure.

Any help is appreciated!

edit: ok, after some more research, i've found that

E(X1 X2] simply means The expectations of X1 and X2 multiplied by each other.

so, what I want to ask now is this.

is the PMF of X1, given that table:

X1 | -1 | 0 | 1 |

px(X1)| 1/3 | 0 | 1/3 |

And finally, how do i find out if X1 and X2 are independent?