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For example, if 20% of the patients in the screening patient are sick (red) and 80% are healthy (blue); and 90% of the sick patients get positive test results; and 30% of the healthy patients get positive test results, we could visualize the probabilities as proportions of a large population, as in the following frequency diagram:\n\n![Frequency diagram](https://i.imgur.com/0XDbrYi.png)\n\nThen, when asking about the probability that a patient with a black tongue depressor is sick, we can divide the number of sick patients with black tongue depressors (18 in this case) by the number of total patients with black tongue depressors (18 + 24, in this case).]\n\nFrequency diagrams, like [1wy waterfall diagrams], provide a way of visualizing [1lz Bayes' Rule]. For example, if 20% of the patients in the screening patient are sick (red) and 80% are healthy (blue); and 90% of the sick patients get positive test results; and 30% of the healthy patients get positive test results, we could visualize the probabilities as proportions of a large population, as in the following frequency diagram:\n\n![Frequency diagram](https://i.imgur.com/0XDbrYi.png)\n\nSee [55z] for a walkthrough of the diagram.\n', metaText: '', isTextLoaded: 'true', isSubscribedToDiscussion: 'false', isSubscribedToUser: 'false', isSubscribedAsMaintainer: 'false', discussionSubscriberCount: '1', maintainerCount: '1', userSubscriberCount: '0', lastVisit: '', hasDraft: 'false', votes: [], voteSummary: [ '0', '0', '0', '0', '0', '0', '0', '0', '0', '0' ], muVoteSummary: '0', voteScaling: '0', currentUserVote: '-2', voteCount: '0', lockedVoteType: '', maxEditEver: '0', redLinkCount: '0', lockedBy: '', lockedUntil: '', nextPageId: '', prevPageId: '', usedAsMastery: 'false', proposalEditNum: '0', permissions: { edit: { has: 'false', reason: 'You don't have domain permission to edit this page' }, proposeEdit: { has: 'true', reason: '' }, delete: { has: 'false', reason: 'You don't have domain permission to delete this page' }, comment: { has: 'false', reason: 'You can't comment in this domain because you are not a member' }, proposeComment: { has: 'true', reason: '' } }, summaries: { Summary: 'Frequency diagrams, like [1wy waterfall diagrams], provide a way of visualizing [1lz Bayes' Rule]. For example, if 20% of the patients in the screening patient are sick (red) and 80% are healthy (blue); and 90% of the sick patients get positive test results; and 30% of the healthy patients get positive test results, we could visualize the probabilities as proportions of a large population, as in the following frequency diagram:\n\n![Frequency diagram](https://i.imgur.com/0XDbrYi.png)\n\nThen, when asking about the probability that a patient with a black tongue depressor is sick, we can divide the number of sick patients with black tongue depressors (18 in this case) by the number of total patients with black tongue depressors (18 + 24, in this case).' }, creatorIds: [ 'NateSoares' ], childIds: [ 'bayes_frequency_diagram_diseasitis' ], parentIds: [ 'bayes_rule' ], commentIds: [], questionIds: [], tagIds: [ 'c_class_meta_tag' ], relatedIds: [], markIds: [], explanations: [ { id: '5150', parentId: 'bayes_frequency_diagram', childId: 'bayes_frequency_diagram_diseasitis', type: 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