The joint PMF contains all the information regarding the distributions of X and Y This means that, for example, we can obtain PMF of X from its joint PMF with Y Indeed, we can write P X ( x) = P ( X = x) = ∑ y j ∈ R Y P ( X = x, Y = y j) law of total probablity = ∑ y j ∈ R Y P X Y ( x, y j) Here, we call P X ( x) the marginal PMF of XSum = sum i/j;J = j j; The Equation Xy 0 In Three Dimensional Space Is Represented By A A Plane B Two Planes At Youtube Generacja x y c jak zarządzać reprezentantami różnych pokoleń