Pricing a joint-life policy requires a joint probability model for two correlated lifetimes. Get the joint distribution wrong and the premium is off by tens of thousands. Exam P tests whether you can build, read, and extract probabilities from joint PMF tables.
For two discrete random variables and , the joint PMF is:
Two properties must hold:
- for all
On the exam, joint PMFs appear as tables. Each cell holds the probability of a specific pair. Row totals and column totals give the marginal distributions.
HIGH-FREQUENCY: Given a table, computing , , or by summing appropriate cells is a core skill.
The joint CDF of and is:
Common mistakes
- Forgetting that is bounded by the sample size. With 2 draws, . Assigning nonzero probability to cells like produces probabilities summing above 1.
- Confusing with . The joint CDF equals the product of marginal CDFs only under independence. In Example 1: , but . Trap: 25/36.
- Summing wrong cells for diagonal events. For , including cell where inflates the answer. Verify each cell's coordinates before including it.
Bottom line
- Joint PMF: , must be non-negative and sum to 1
- Joint CDF: , cumulate down and to the left across every qualifying cell
- Rectangle formula:
- Independence test: must hold for EVERY cell
Exam shortcut
When handed a joint PMF table, immediately compute row and column totals in the margins. For diagonal events like , draw a diagonal line across the table to separate qualifying cells visually. "CDF = Cumulate Down and Left, Four terms for rectangles." . "Every cell must multiply out" for independence. Row total times column total. One mismatch proves dependence.
The full lesson (about 3,020 words, 20 min read) adds 3 worked examples, all 7 common mistakes, a self-check, free in the app.
Learning objectives
- 3a
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