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Hatshy [7]
2 years ago
6

Roy has a bag containing green, blue, red, brown, and black marbles. He randomly picks a marble and replaces it. He repeats this

experiment 60 times and records the results in this table.

Mathematics
1 answer:
Novosadov [1.4K]2 years ago
6 0

Answer:

Green: 0.3

Blue: 0.1

Red: 0.35

Brown: 0.15

Black: 0.1

cannot

Step-by-step explanation:

Hi, thank you for posting your question here in Brainly.

To find the probability of an event, you have to divide the number of trials of that event that succeeded to the total number of trials. Based on that definition, the probability would be 18/60=0.3, 6/60=0.1, 21/60=0.35, 9/60=0.15, 6/60=0.1

I hope i helped you out and helped you learn something new :)

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Step-by-step explanation:

You're given that line DE and line FG are parallel and KL and FG are perpendicular. Then you can find out angle ∠BAC by using the vertical angles property: ∠BAC=62°. Then since KL and FG are perpendicular ∠ABC = 90°. So you find the angle ∠BCA by finding the sum of interior angles: 62+90+∠BCA=180, therefore ∠BCA is 28°. Finally, ∠x or ∠JCG = 28 because ∠JCG and ∠BCA are vertical angles and congruent.

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Please answer the image below
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<h2>301.593</h2><h2 />

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<u>plugin values into the formula</u>

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The number of people arriving at a ballpark is random, with a Poisson distributed arrival. If the mean number of arrivals is 10,
Stella [2.4K]

Answer:

a) 3.47% probability that there will be exactly 15 arrivals.

b) 58.31% probability that there are no more than 10 arrivals.

Step-by-step explanation:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}

In which

x is the number of sucesses

e = 2.71828 is the Euler number

\mu is the mean in the given time interval.

If the mean number of arrivals is 10

This means that \mu = 10

(a) that there will be exactly 15 arrivals?

This is P(X = 15). So

P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}

P(X = 15) = \frac{e^{-10}*(10)^{15}}{(15)!} = 0.0347

3.47% probability that there will be exactly 15 arrivals.

(b) no more than 10 arrivals?

This is P(X \leq 10)

P(X \leq 10) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5) + P(X = 6) + P(X = 7) + P(X = 8) + P(X = 9) + P(X = 10)

P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}

P(X = 0) = \frac{e^{-10}*(10)^{0}}{(0)!} = 0.000045

P(X = 1) = \frac{e^{-10}*(10)^{1}}{(1)!} = 0.00045

P(X = 2) = \frac{e^{-10}*(10)^{2}}{(2)!} = 0.0023

P(X = 3) = \frac{e^{-10}*(10)^{3}}{(3)!} = 0.0076

P(X = 4) = \frac{e^{-10}*(10)^{4}}{(4)!} = 0.0189

P(X = 5) = \frac{e^{-10}*(10)^{5}}{(5)!} = 0.0378

P(X = 6) = \frac{e^{-10}*(10)^{6}}{(6)!} = 0.0631

P(X = 7) = \frac{e^{-10}*(10)^{7}}{(7)!} = 0.0901

P(X = 8) = \frac{e^{-10}*(10)^{8}}{(8)!} = 0.1126

P(X = 9) = \frac{e^{-10}*(10)^{9}}{(9)!} = 0.1251

P(X = 10) = \frac{e^{-10}*(10)^{10}}{(10)!} = 0.1251

P(X \leq 10) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5) + P(X = 6) + P(X = 7) + P(X = 8) + P(X = 9) + P(X = 10) = 0.000045 + 0.00045 + 0.0023 + 0.0076 + 0.0189 + 0.0378 + 0.0631 + 0.0901 + 0.1126 + 0.1251 + 0.1251 = 0.5831

58.31% probability that there are no more than 10 arrivals.

8 0
3 years ago
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