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Assessing the Effect of Visualizations on Bayesian Reasoning through Crowdsourcing

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## Assessing the Effect of Visualizations on Bayesian Reasoning through Crowdsourcing

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**Assessing the Effect of Visualizationson Bayesian Reasoning**through Crowdsourcing LuanaMicallef Pierre Dragicevic Jean-Daniel Fekete**The probability that a woman at age 40 has breast cancer is**1%. The probability that the disease is detected by a mammography is 80%. The probability that the test misdetects the disease although the patient does not have it is 9.6%. If a woman at age 40 is tested as positive, what is the probability that she indeed has breast cancer? 0% - 30% 30% - 60% 60% - 100%**The probability that a woman at age 40 has breast cancer is**1%. The probability that the disease is detected by a mammography is 80%. The probability that the test misdetects the disease although the patient does not have it is 9.6%. If a woman at age 40 is tested as positive, what is the probability that she indeed has breast cancer? 0% - 30% 30% - 60% 60% - 100%**The probability that a woman at age 40 has breast cancer is**1%. The probability that the disease is detected by a mammography is 80%. The probability that the test misdetects the disease although the patient does not have it is 9.6%. If a woman at age 40 is tested as positive, what is the probability that she indeed has breast cancer? 0% - 30% 30% - 60% 60% - 100%**95 doctors out of 100**said the answer is between70% to 80%**Why**the correct answer is so low**Bayes’ Theorem**P ( cancer | +ve mammography ) = P ( +ve mammography | cancer) P (+ve mammography | cancer) + P (+ve mammography | cancer)**The probability that a woman at age 40 has breast cancer is**1%. women with cancer women without cancer**If a woman at age 40 is tested as positive, what is the**probability that she indeed has breast cancer? The probability that the disease is detected by a mammography is 80%. The probability that the test misdetects the disease although the patient does not have it is 9.6%. 7.8% women with cancer women without cancer**Can such**visualizations facilitate Bayesian reasoning**contingency table**signal detection curves trees Bayesian boxes bar-grain boxes**+**Euler diagram frequency grid**Previous Studies**Mainly in Psychology Claim that Bayesian problem representation impacts comprehension**but …**InconsistentfindingsMost effective Bayesian problem representation? UNCLEAR Inconsistent and sometimes inappropriate diagram designs Diagrams do not match textual information**Area-Proportional**Not Area-Proportional**and the subjects …**Specific background usually highly-focused university students Specific age group Sometimes, specific department carried out as part of their course**so …**• cannotgeneralize their findings toa more diverse population of laypeople**Our Work**Assessing the Effect of Visualizations on Bayesian Reasoning through Crowdsourcing**to identify…**• - the most effective visualization for the crowd • - whether hybrid visualizations are helpful • - the link between the visualizations and different spatial and numeracy abilities**but…**• how appropriate is**Amazon MTurk**Used and evaluated for research and InfoVis Demographics of workers are well-understood Captures aspects of real-world problem solving better - alarge diverse population with different backgrounds, education, occupations, age, gender - workers carry out tasks rapidly but accurately to improve their rating - reduces experimental biases, as demand characteristics**168 workers**with MTurk approval rate ≥ 95%**25 min**$1**3 Bayesian problems**classics in Psychology in natural frequencies format**followed by**• objective and subjective numeracy tests • paper folding spatial abilities test • brief questionnaire