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yawa3891 [41]
3 years ago
14

A bag contains 6 red marbles, 4 black marbles, 10 green marbles, and 2 blue marbles. Marbles are taken at random from the bag, o

ne at a time, and then replaced. Find the probability of drawing a black marble, then drawing a green marble.
A 2/11
B 7/11
c 10/121
d 20/231​
Mathematics
1 answer:
Inga [223]3 years ago
4 0

Answer:

B

Step-by-step explanation:

First you will add them all up

6+4+10+2=22

Second find the black and green amount and add them together

4+10=14

Thirdly turn this into a fraction

14/22

Lastly simplify

14/11 / 2 = 7/11

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What is the end of your proof? (What are you proving?)
AnnyKZ [126]

Answer

with

Step-by-step explanation:

Statement      Reasons

1.∠1 ≅ 4             Given

2.∠1 = ∠2           Being Vertically opposite angles.

3.∠4 = ∠3          Being Vertically opposite angles.  

4.∠2 = 3             From Statement no 2 & 3, Transitive property.

5.∠2 ≅ 3            From Statement 4

Proved.

6 0
2 years ago
Graph the quadratic function f(x)=2x^2+16x+30 .
kondor19780726 [428]
See the attached picture:

4 0
3 years ago
Helpppppp !!!!!!!!!!!
horrorfan [7]

Answer:

A

Step-by-step explanation:

The total amount equals 40 when added together and the yellow is 5. 40 divided by 5 is 8 which makes 1/8

4 0
3 years ago
Let X denote the length of human pregnancies from conception to birth, where X has a normal distribution with mean of 264 days a
Kaylis [27]

Answer:

Step-by-step explanation:

Hello!

X: length of human pregnancies from conception to birth.

X~N(μ;σ²)

μ= 264 day

σ= 16 day

If the variable of interest has a normal distribution, it's the sample mean, that it is also a variable on its own, has a normal distribution with parameters:

X[bar] ~N(μ;σ²/n)

When calculating a probability of a value of "X" happening it corresponds to use the standard normal: Z= (X[bar]-μ)/σ

When calculating the probability of the sample mean taking a given value, the variance is divided by the sample size. The standard normal distribution to use is Z= (X[bar]-μ)/(σ/√n)

a. You need to calculate the probability that the sample mean will be less than 260 for a random sample of 15 women.

P(X[bar]<260)= P(Z<(260-264)/(16/√15))= P(Z<-0.97)= 0.16602

b. P(X[bar]>b)= 0.05

You need to find the value of X[bar] that has above it 5% of the distribution and 95% below.

P(X[bar]≤b)= 0.95

P(Z≤(b-μ)/(σ/√n))= 0.95

The value of Z that accumulates 0.95 of probability is Z= 1.648

Now we reverse the standardization to reach the value of pregnancy length:

1.648= (b-264)/(16/√15)

1.648*(16/√15)= b-264

b= [1.648*(16/√15)]+264

b= 270.81 days

c. Now the sample taken is of 7 women and you need to calculate the probability of the sample mean of the length of pregnancy lies between 1800 and 1900 days.

Symbolically:

P(1800≤X[bar]≤1900) = P(X[bar]≤1900) - P(X[bar]≤1800)

P(Z≤(1900-264)/(16/√7)) - P(Z≤(1800-264)/(16/√7))

P(Z≤270.53) - P(Z≤253.99)= 1 - 1 = 0

d. P(X[bar]>270)= 0.1151

P(Z>(270-264)/(16/√n))= 0.1151

P(Z≤(270-264)/(16/√n))= 1 - 0.1151

P(Z≤6/(16/√n))= 0.8849

With the information of the cumulated probability you can reach the value of Z and clear the sample size needed:

P(Z≤1.200)= 0.8849

Z= \frac{X[bar]-Mu}{Sigma/\sqrt{n} }

Z*(Sigma/\sqrt{n} )= (X[bar]-Mu)

(Sigma/\sqrt{n} )= \frac{(X[bar]-Mu)}{Z}

Sigma= \frac{(X[bar]-Mu)}{Z}*\sqrt{n}

Sigma*(\frac{Z}{(X[bar]-Mu)})= \sqrt{n}

n = (Sigma*(\frac{Z}{(X[bar]-Mu)}))^2

n = (16*(\frac{1.2}{(270-264)}))^2

n= 10.24 ≅ 11 pregnant women.

I hope it helps!

6 0
3 years ago
On a number line, which number is 7/9 of the way from -6 to 3
Paha777 [63]

Answer:

1?

Step-by-step explanation:

if you go from -6 to 3 it is 9 spaces. so 7 spaces equals one.

4 0
3 years ago
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