Answer:
the probability the car was actually blue as claimed by the witness is 33.33%. This is a low percentage and thus, there is a reasonable doubt about the guilt of the client.
Step-by-step explanation:
We are given;
P(car is blue) = 1% = 0.01
P(car is green) = 99% = 0.99
P(witness said blue | car is blue) = 99% = 0.99
P(witness said blue | car is green) = 2% = 0.02
We will solve this by using Bayes’ formula for inverting conditional probabilities:
Thus;
P(car is blue | witness said blue) =
[P(witness said blue | car is blue) × P(car is blue)] / [(P(witness said blue | car is blue) × P(car is blue)) + (P(witness said blue | car is green) × P(car is green))]
Plugging in the relevant values gives;
(0.99 × 0.01)/((0.99 × 0.01) + (0.02 × 0.99)) = 0.3333
Thus, the probability the car was actually blue as claimed by the witness is 0.3333 or 33.33%
Answer:
Option A = 75 is the best option
Step-by-step explanation:
It took Ashlie 2.5 hours (11:30 am - 2pm) to assemble the marketing packets
Rate = Number of jobs done/Time taken = 90 packages/hr
Number of jobs done = Rate * Time taken = 90 * 2.5 = 225 packages.
Dwayne has assembled the same number of packages = 225 (as reported in the question),
It took Ashlie 2.5 hours (11 am - 2pm)
Then, his work rate is calculated as: Number of jobs done/Time taken = 225 packages/3 hours = 75
Thus, option A = 75 is the best option
For this question you should know that you can multiply both number in 1/4 by 3 and you will have:
1*3 / 4*3 = 3/12
so the answer is yes they are equivalent :)))
i hope this is helpful
have a nice day
Part a is correct.
Part b can be done a couple ways.
1) Use binomial distribution. p = 0.2, n = 144
P(x>3) = 1 - P(x=0) -p(x=1) -p(x=2) -p(x=3)
where
2) Assume a normal distribution with mean = 28.2, stdev = 4.8
Look up z-value in normal table to find probability.
Hope that helps.
