has tested positive for a disease and wants to know the probability she actually is sick...
2. A rare disease affects 1% of the population. A test has a sensitivity of 98%, i.e., it will give a positive result 98% of the time that a person actually has the disease. The same test also has a specificity of 95%, i.e., it will give a negative result 95% of the time when a person does not have the disease. Denote the event that a randomly person has a disease by D, and the event that a randomly...
Medical screening tests are used to check for the presence on disease, evidence of illegal drug use, etc. The its sensitivity and its specificity. The sensitivity among those with the condition that will test positive. The specichy proportion among those without the condition that will test neg sensitivity of a test is defined to be the conditional ng those without the condition that will test negative. More formally, the test is defined to be the conditional probability that a person...
A lab test produces a positive result with 90% probability when the patient is actually sick and with 10% if the patient is healthy. It is known that 15% of the population is sick. (a) What is the joint probability function of patients’ health and test results? (b) If the test is positive, what is the probability that the patient is actually sick? (c) The probability you just calculated in part 1b is the _____ probability of ____ given _____.
The results for a blood test for a certain disease are shown. Blood Test Sick POS NEG Total Yes 34 5 39 No 1025 3795 4820 Total 1059 . 3800 4859 a. Estimate the probability that the sickness occurs. b. Find the estimated (i) sensitivity P(POS|Yes), (ii) specificityP(NEG|No). c. Find the estimated (i) P(Yes|POS), (ii) P(Yes| NEG) d. Explain how the probabilities in parts b and c give four ways of describing the probability that a diagnostic test makes a...
3. Assume 6% of people have a certain disease. A test gives correct diagnosis with probability 0.85 i.e. if the person is sick, the test will be positive with probability 0.85, but if the person is not sick, the test will be positive with probability 0.15. A random person from the population has tested positive for the disease. What is the probability that he is actually sick? Part 2. Random Variables
12. Suppose 500 athletes are tested for a drug, one in twenty has used the drug, the test has a 98% specificity and the test has a 100% sensitivity. That is, the probability of a false positive is 2% and there is no chance that the user of the drug will go undetected. Construct a tree diagram showing the probabilities associated with this problem. Write a probability on each branch (6 branches). Multiply the the probabilities along each path and...
12. Suppose 500 athletes are tested for a drug, one in twenty has used the drug, the test has a 98% specificity and the test has a 100% sensitivity. That is, the probability of a false positive is 2% and there is no chance that the user of the drug will go undetected. Construct a tree diagram showing the probabilities associated with this problem. Write a probability on each branch (6 branches). Multiply the the probabilities along each path and...
Jane is being tested for a rare disease. Only 1.5% of the population has the disease. The following data were collected. First a group of people who had the disease were tested. 98.5% tested positive and 1.5% tested negative. Next, a group of people who did not have the disease were tested. 3% tested positive and 97% tested negative. (First write down the six given probabilities) [1] Page 4 of 8 MATH 140 - Introduction to Statistics What is the...
Negative predictive value is a probability of not having disease given that you have just tested negative and is expressed as O a. True negative/(True negative False Positive) O b. True positive/(True positive False Negative) О c. True Negative/(True negative + False Negative) O d. True positive/True positive False Positive) QUESTION 10 Positive predictive value is the probability that subjects with a positive screening test truly have the disease. The equation for positive predictive value is expressed as: O 3....
Suppose that a patient is being tested for a disease and it is known that 1% of population have the disease. Suppose also that the patient tests positive and that the test is 95% accurate. Let D be the event that the patient has the disease and T the event that the tests positive. Then we know P(T|D) = P(T’|D’) = 0.95. Using Baye’s theorem and the Law of Total Probability, determine the prbability that the patient actually has the...