The answer is 3/4.
25% of the 200 jelly beans are green, by converting 25% into a decimal and multiplying it by the total amount of jelly beans, you can find the amount of jelly beans that are green.
25% = 0.25
200 x 0.25 = 50
Therefore 50 of the jelly beans are green.
The question wants to know the probability of the jelly bean being picked is not green.
200 - 50 = 150 jelly beans not green
Finding the probability:
150/200 = 3/4
2y plus 4x= z
2y plus 4x -4x= z-4x
2y\2= z-4x\2
y=z-4x\2
so what i did was a long process but it worked i started by taking $5550 and multiplying it by .12 which gave me $666 then i did 9500-5550=3950 then i took 3950 and multiplied it by .09 and it gave me 355.5 then i added those together and got 1021.5 so i needed to increase the amount i invested at 12% to get a higher yield. i did this process a few more times and each time i increase the amount of money i invested at 12% by 25 dollars and i finally arrived at:
5900 x .12 = $708
9500-5900=3600
3600 x .09 =$324
708+324= $1032
so your answer is that you invested $5900 at 12% and $3600 at 9%.
add me as a friend if you like because i am generally good at math. hope this helped.
Answer:
The probability is 0.0005.
Explanation:
The stated question is incomplete. The complete question is as follows.
<em>A manufacturer is developing a new type of paint. Test panels were exposed to various corrosive conditions to measure the protective ability of the paint. Based on the results of the test, the manufacturer has concluded that the mean life before corrosive failure for the new paint is 155 hours with a standard deviation of 27 hours. If the manufacturer's conclusions are correct, find the probability that the paint on a sample of 65 test panels will have a mean life before corrosive failure of less than 144 hours. </em>
The mean life is 155 hours. Hence, μ = 155.
The standard deviation is 27 hours. Hence, σ = 27.
The sample size in 65 test panels. Hence, n = 65.
We can use the central limit theorem to find the probability that the mean life before corrosive failure is less than 144 hours. By the central limit theorem:
P(X < 144) = P[(X - μ) / (σ / √n) < (144 - 155) / (27/√65)]
P(X < 144) = P(Z < -3.2846)
Using the Z-value table for normal distribution, this value turns out to be:
P(X < 144) = 0.0005
Answer:
3 Quadrant
2 Quadrant
4 Quadrant
They are Collinear.
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