# Joint Probability Table

A Joint Probability Table is a joint probability structure that is a probability mass function structure (a probability function structure of the conditional probability values and marginal probability values for random variables).

**Context:**- It can range from being a Discrete Joint Probability Structure to being a Continuous Joint Probability Structure.
- …

**Examples(s):**- for Two dice roll experiments:
**H****T****Sum****H**21.5% 25.1% 46.6% **T**25.2% 25.2% 50.4% **Sum**46.7% 50.3% 100%

- for Two dice roll experiments:
**Counter-Example(s):****See:**Joint Probability.

## References

### 2009

- (Spiegel et al., 2009) ⇒ Murray R. Spiegel, John J. Schiller, and R. Alu Srinivasan. (2009). “Probability and Statistics - Schaum's outlines, Edition 3." McGraw-Hill Professional. ISBN:0071544259
- QUOTE: A joint probability function for
*X*and*Y*can be represented by a*joint probability table*as in Table 2-3. The probability that [math]X = x_j[/math] is obtained by adding all entries in the row corresponding to [math]x_i[/math] and is given by [math]P(X=x_j)=f_1(X_j)=\sum_{n}^{k-1}f(x_j, y_k)[/math].

- QUOTE: A joint probability function for

### 1987

- (Hogg & Ledolter, 1987) ⇒ Robert V. Hogg, and Johannes Ledolter. (1987). “Engineering Statistics." Macmillan Publishing. ISBN:0023557907
- QUOTE: Probabilities such as … are called marginal probabilities because they are usually recorded in the margins of a joint probability table.