Table 1.

Problem formulations for the breast cancer screening contexts

	Breast cancer screening problem
	Probability version	Natural frequency version
Medical situation	Imagine that you are a physician in a mammography screening center where women without symptoms are screened with mammograms for breast cancer
	At the moment, you are advising a woman who has no symptoms but who has received a positive result from her mammogram. This woman wants to know what this result mean for her
	For your answer, there is the following information available, which is bases on a random sample of women who have all undergone a mammography
Presentation of information	•Text only	•Text only
	•Tree diagram only	•Tree diagram only
Text	The probability of breast cancer is 1% for a woman of a particular age group who participates in a routine screening. If a woman who participates in a routine screening has breast cancer, the probability is 80% that she will have a positive mammogram. If a woman who participates in a routine screening does not have breast cancer, the probability is 9.6% that she will have a false-positive mammogram	100 out of 10,000 women of a particular age group who participate in a routine screening have breast cancer. 80 out of 100 women who participate in a routine screening and have breast cancer will have a positive mammogram. 950 out of 9,900 women who participate in a routine screening and have no breast cancer will have a false-positive mammogram
Tree diagram	Probability tree (in the version with a tree diagram)	Frequency tree (in the version with a tree diagram)
Question	What is the probability that a woman with a positive mammogram actually has breast cancer?	How many of the women with a positive mammogram actually have breast cancer?
	Answer: _______	Answer: ____ out of _____