L3 (a) 1-3. In 2010, in the U.S., the pregnancy rate among women 15-44 was 9.8%. There are many pregnancy tests out there. Nancy decided to use AccuBaby, because she saw the relatively high "accuracy" number (97% accurate). Accuracy is often misunderstood and confused with other measures like sensitivity and precision. We will interpret accuracy as the probability that a woman who is pregnant tests positive, and the probability of receiving a negative result if she is not pregnant. That is Pr(0/P) Pr(e/NP)-o.97. Looking at the tree diagram below accuracy refers to the probability along the branches and 0.97 田 0.098 0.97 Nancy wants to know the probability that she is pregnant if the test comes out positive, that is, Pr (Pl) Pr (pregnant given positive) [This value is called the positive predictive value]. She also wants to know the probability that she is not pregnant if the test comes out negative, that is, Pr (NIe) Pr (not pregnant given negative) [This value is called the negative predictive value]. Let's help her out. (a) Label all unlabeled branches with the proper probabilities 1-3. In 2010, in the U.S., the pregnancy rate among women 15-44 was 9.8%. There are many pregnancy tests out there. Nancy decided to use AccuBaby, because she saw the relatively high "accuracy" number (97% accurate). Accuracy is often misunderstood and confused with other measures like sensitivity and precision. We will interpret accuracy as the probability that a woman who is pregnant tests positive, and the probability of receiving a negative result if she is not pregnant. That is Pr(0/P) Pr(e/NP)-o.97. Looking at the tree diagram below accuracy refers to the probability along the branches and 0.97 田 0.098 0.97 Nancy wants to know the probability that she is pregnant if the test comes out positive, that is, Pr (Pl) Pr (pregnant given positive) [This value is called the positive predictive value]. She also wants to know the probability that she is not pregnant if the test comes out negative, that is, Pr (NIe) Pr (not pregnant given negative) [This value is called the negative predictive value]. Let's help her out. (a) Label all unlabeled branches with the proper probabilities