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- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Introductory_Statistics_(Lane)/05%3A_Probability/5.12%3A_Base_RatesCompute the probability of a condition from hits, false alarms, and base rates using a tree diagram. Compute the probability of a condition from hits, false alarms, and base rates using Bayes' Theorem
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Introductory_Statistics_(Lane)/05%3A_Probability/5.13%3A_Bayes_DemoThis demonstration lets you examine the effects of base rate, true positive rate, and false positive rate on the probability that a person diagnosed with disease X actually has the disease. The base r...This demonstration lets you examine the effects of base rate, true positive rate, and false positive rate on the probability that a person diagnosed with disease X actually has the disease. The base rate is the proportion of people who have the disease. The true positive rate is the probability that a person with the disease will test positive. The false positive rate is the probability that someone who does not have the disease will test positive.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/OpenIntro_Statistics_(Diez_et_al)./02%3A_Probability/2.02%3A_Conditional_Probability_ISimilarly, the test gives a false positive in 7% of patients who do not have breast cancer: it indicates these patients have breast cancer when they actually do not.39 If we tested a random woman over...Similarly, the test gives a false positive in 7% of patients who do not have breast cancer: it indicates these patients have breast cancer when they actually do not.39 If we tested a random woman over 40 for breast cancer using a mammogram and the test came back positive { that is, the test suggested the patient has cancer { what is the probability that the patient actually has breast cancer?
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/OpenIntro_Statistics_(Diez_et_al)./02%3A_Probability/2.03%3A_Conditional_Probability_IINext, we identify two probabilities from the tree diagram. (1) The probability that there is a sporting event and the garage is full: 0.14. (2) The probability the garage is full: \(0.0875 + 0.14 + 0....Next, we identify two probabilities from the tree diagram. (1) The probability that there is a sporting event and the garage is full: 0.14. (2) The probability the garage is full: 0.0875+0.14+0.0225=0.25. Exercise 2.60 In Exercise 2.57 and 2.59, you found that if the parking lot is full, the probability a sporting event is 0.56 and the probability there is an academic event is 0.35.
