A marginal distribution keeps one variable. To keep X, add the joint masses across all Y values.
Figure 1The joint table rows X=0,1 and columns Y=0,1 are (0.1,0.2) and (0.3,0.4). The right-hand P(X) cells are 0.3 and 0.7: the sums of the corresponding joint rows. Summing removes the Y coordinate while retaining every X value.
Marginalization adds probability mass. No division is needed: the complete marginal already sums to 1. Use the table headings to choose which coordinate to keep.
Check your reasoning
Y: cache flag. X rows; Y columns; order 0,1. Joint rows: (0.3,0.2);(0.1,0.4). Give the cache flag PMF.
A(0.5,0.5)
B(0.3,0.2)
C(0.4,0.6)
Show answer and explanation
(0.4,0.6)
Columns: (0.4,0.6).
Key takeaway
Keep one variable; sum over the other.
Marginalize a joint mass table over one variable.
Further questions
Does a marginal depend on which row is observed?
No. It sums over the other variable without observing or fixing it.