See also Gerd Gigerenzer&#x27;s book &quot;Reckoning with Risk&quot;.<p><a href="https:&#x2F;&#x2F;plus.maths.org&#x2F;content&#x2F;reckoning-risk" rel="nofollow">https:&#x2F;&#x2F;plus.maths.org&#x2F;content&#x2F;reckoning-risk</a><p>&gt;The probability that one of these women [asymptomatic, aged 40 to 50, from a particular region, participating in mammography screening] has breast cancer is 0.8 percent. If a woman has breast cancer, the probability is 90 percent that she will have a positive mammogram. If a woman does not have breast cancer, the probability is 7 percent that she will still have a positive mammogram. Imagine a woman who has a positive mammogram. What is the probability that she actually has breast cancer?<p>&gt; Eight out of every 1,000 women have breast cancer. Of these 8 women with breast cancer, 7 will have a positive mammogram. Of the remaining 992 women who don&#x27;t have breast cancer, some 70 will still have a positive mammogram. Imagine a sample of women who have positive mammograms in screening. How many of these women actually have breast cancer?<p>His point is that it&#x27;s not just patients who don&#x27;t know the numbers.  Doctors and nurse, who use these numbers every day, also don&#x27;t understand them.