Anew screening test for lyme disease is developed for use in the general population. the sensitivity and specificity of the new test are 60% and 70%, respectively. three hundred people are screened at a clinic during the first year the new test is implemented. assume the true prevalence of lyme disease among clinic attendees is 10%. the predictive value of a positive test is: 33.0% 18.2% 94.0% 22.2% 6.0%

The positive predictive value is 18.2%

Step-by-step explanation:

Let TP (true positive) denote the Sensitivity, and TN (true negative) denote the Specificity, and P prevalence. The Positive Predictive Value is calculated as follows:

The positive predictive value is 18.2%

the answer   is 200

step-by-step explanation:

this is a problem about poisson probabilities.   i don't know if you've

already studied poisson distributions, or if you have a place to look

to read more about the subject.  

here's how you can see a poisson distribution coming.   when there are

a lot of events that may happen at any time (or any place), and when

you're counting how many of them happen at a particular time (or a

particular place), and each event is independent of the others, then

the result is a poisson distribution.   this is roughly true for the

chocolate chips; one chip being in a cookie has only a small effect on

the probability that another chip will be in the cookie.

once you know you have a poisson distribution, you know a lot.   there

is only one parameter to a poisson distribution, so if you know the

mean, you know everything.   the form of the distribution is

  probability of n chips = {[e^(-x)]*(x^n)} / (n! )

i am sorry it just submitted an answer but the answer is 365 boys. hopes this

step-by-step explanation: