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Marginal table

As explained in Fabulous Adventures in Data Structures and Algorithms

A marginal table is a tabular summary whose row and column margins show aggregate totals for the variables being analyzed.

A marginal table organizes survey counts by variables while placing aggregate totals along the row and column margins. Those totals answer probability questions before or after additional evidence is observed. section 13.1

Cold and sneezing survey

In a survey of 10,000 people, the margins show that 1,000 have colds, establishing a 10% prior probability. Among the 1,000 people with colds, 860 sneezed, giving P(S|C) = 86%. section 13.1

Table 13.1 A survey of 10,000 respondents organized in a marginal table

Cold: YES

Cold: NO

Total

Sneezed: YES

860

270

1,130

Sneezed: NO

140

8,730

8,870

Total

1,000

9,000

10,000

Use the table to trace how row and column totals support prevalence estimates and conditional-probability calculations. section 13.1

How Fabulous Adventures in Data Structures and Algorithms covers it

How deep it goes
Explains margins through a worked survey, then uses totals to derive prior and conditional probabilities.
Examples
Uses a 10,000-person cold-and-sneezing survey with row totals, column totals, and conditional-probability calculations.
What you can do after
Evaluate/understand prevalence and conditional probabilities by reading aggregate totals from a survey table.
How it connects
Connects aggregate margins to prior probability, conditional probability, prevalence, evidence, and Bayes’ theorem.
Cover of Fabulous Adventures in Data Structures and Algorithms
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