Answer:
Required Probability = 0.605
Step-by-step explanation:
Let Probability of people actually having predisposition, P(PD) = 0.03
Probability of people not having predisposition, P(PD') = 1 - 0.03 = 0.97
Let PR = event that result are positive
Probability that the test is positive when a person actually has the predisposition, P(PR/PD) = 0.99
Probability that the test is positive when a person actually does not have the predisposition, P(PR/PD') = 1 - 0.98 = 0.02
So, probability that a randomly selected person who tests positive for the predisposition by the test actually has the predisposition = P(PD/PR)
Using Bayes' Theorem to calculate above probability;
P(PD/PR) =
=
=
= 0.605 .
Cost of the current plan: $175
Number of devices: x
Cost of the new plan: $94+($4.50/device)x
Cost of the new plan is less than the current plan:
$94+($4.50/device)x<$175
Solving for x:
$94+($4.50/device)x-$94<$175-$94
($4.50/device)x<$81
(device/$4.50)($4.50/device)x<(device/$4.50)($81)
x<18 devices
Please, see the attached file.
Thanks.
Answer:
Solution in photo
Step-by-step explanation:
Answer:
I think it says B; the one in the bottom left. Both B and D are linear functions, but D is a linear function of only y, not x. Therefore, the answer is B.
Step-by-step explanation:
The answer to this question is A