One of the most prolific types of false positives in the medical field come from breast cancer screenings (mammograms). In the United States, the rate of false positive mammograms Is up to 18% Screenings, The null hypothesis Would be that the patient does not have breast cancer. Describe type one and type 2 errors and their consequences of each in context of Breast cancer screenings. Discuss which one you think is more serious.

0.16 or 16%

step-by-step explanation:

lets take a coin for example.

if you toss it twice, it has a 1/4 chance of landing on heads both times because 1/2 * 1/2 is 1/4.

with the cards, the chance of picking dog is 0.4. having two people pick one is like picking a card twice in a row. so 0.4 * 0.4 is 0.16, or 16%

tried on you are knowing that we can't leave the picture in the graph ok no problem now you need to send it in the question group