Index: The Book of Statistical Proofs ▷ Statistical Models ▷ Count data ▷ General contingency table ▷ Definition

Definition: Let $A$ and $B$ be categorical random variables with their possible values denoted by random events $A_1, \ldots, A_k$ and $B_1, \ldots, B_l$, respectively. Then, (i) the set of relative frequencies of $A$’s and $B$’s outcomes’ occurences or (ii) the set of absolute frequencies of all combinations of $A_1, \ldots, A_k$ and $B_1, \ldots, B_l$ in a sample is referred to as a contingency table.

Observed data from a $k \times l$ contingency table are characterized as follows:

  • $y_{ij}$ for $i \in \left\lbrace 1,\ldots,k \right\rbrace$ and $j \in \left\lbrace 1,\ldots,l \right\rbrace$ is the number of cases in which $A_i$ and $B_j$;

  • $y_{i \bullet} = \sum_{j=1}^l y_{ij}$ is the (marginal total) number of cases in which $A_i$;

  • $y_{\bullet j} = \sum_{i=1}^k y_{ij}$ is the (marginal total) number of cases in which $B_j$;

  • $n = \sum_{i=1}^k \sum_{j=1}^l y_{ij}$ is the total number of cases.

The distribution underlying a $k \times l$ contingency table is characterized as follows:

  • $p_{ij}$ for $i \in \left\lbrace 1,\ldots,k \right\rbrace$ and $j \in \left\lbrace 1,\ldots,l \right\rbrace$ is the joint probability that $A_i$ and $B_j$;

  • $p_{i \bullet}$ is the marginal probability that $A_i$;

  • $p_{\bullet j}$ is the marginal probability that $B_j$;

  • $1 = \sum_{i=1}^k \sum_{j=1}^l p_{ij}$ is the probability of the sample space.

 
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Metadata: ID: D242 | shortcut: ct | author: JoramSoch | date: 2026-09-18, 09:51.