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Gekata [30.6K]
3 years ago
14

You have a bag with 4 pairs of socks. There are 2 red pairs and 2 black pairs. You pull a sock from the bag and put it back 3 ti

mes. What is the probability that you pull out a red sock each time?
Mathematics
1 answer:
eduard3 years ago
7 0
Total Number of socks = 4 pairs= 8 socks
Number of red socks = 4
Number of black socks = 4

Probability of pulling a red sock from the bag the first time =  \frac{4}{8}= \frac{1}{2}

Since the sock is placed back in the bag before pulling a sock again, the number of socks remains the same.

So,

Probability of pulling a red sock from the bag the second time =  \frac{4}{8}= \frac{1}{2}

And

Probability of pulling a red sock from the bag the third time =  \frac{4}{8}= \frac{1}{2}

Therefore, the probability of pulling a red sock 3 times from the bag = \frac{1}{2}*  \frac{1}{2}*  \frac{1}{2}= \frac{1}{8}
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The answer is the first choice.

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What are two equivalent fractiond for 30/10
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Answer:

The answer is 3/1 or 3

Step-by-step explanation:

30/10 = 3/1 = 3

Thus, The answer is 3/1 or 3

<u>-TheUnknownScientist</u><u> 72</u>

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2 years ago
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Plss help I’ll mark brainliest
melamori03 [73]

Answer:

D 6

Step-by-step explanation:

Normally when I multiply mixed numbers, I change them to improper fractions first so that it is easier.

1\frac{2}{10} × 5 = \frac{12}{10} × 5

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Change back to simplest form.

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2 years ago
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Listed below is data on profit and market capitalization for a sample of 15 different firms in U.S. Profit is the y variable and
MissTica

Answer:

Step-by-step explanation:

Hello!

You have two study variables:

Dependent variable

Y: Profit of the firm in the U.S.

Independent variable

X: Market capitalization of the firm

a.

See the scatterplot in the attachment.

Looking at the graphic it seems that there is a positive regression between the profit and the market capitalization, meaning that every time the market capitalization of the firm increases, the profit of this firm also increases. But not all the "firms" adjust linearly, so I wouldn't expect the regression to be powerful.

b.

The regression model is E(Yi)= α + βXi

Where the parameters of the model are α and β, these two parameters are to be estimated to estimate the regression equation. The estimator for α is a and the estimator for β is b:

a= Y[bar] - bX[bar]

b= [∑XY-(∑X*∑Y)/n]/[∑X²-(∑X)²/n]

I'll use a statistic software to calculate the estimated regression equation:

^Yi= a + bXi

^Yi= 325.89 + 0.07Xi

c.

You need to predict the value of Y (Profit) given a value of X= 70721.3 (million). To make this prediction you have to use the estimated equation:

^Yi= 325.89 + 0.07Xi

^Yi= 325.89 + 0.07(70721.3)= 5276.381

The predicted profit for a market capitalization value of 70,721.3 is 5276.381 million.

I hope this helps!

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\bf \textit{equation of a circle}\\\\ (x- h)^2+(y- k)^2= r^2 \qquad center~~(\stackrel{}{ h},\stackrel{}{ k})\qquad \qquad radius=\stackrel{}{ r} \\\\[-0.35em] \rule{34em}{0.25pt}\\\\ (x-9)^2+y^2=4\implies (x-\stackrel{h}{9})^2+(y-\stackrel{k}{0})^2=2^2~\hfill \stackrel{center}{(9,0)} \\\\\\ (x-\stackrel{h}{3})^2+(y-\stackrel{k}{2})^2=4\implies (x-\stackrel{h}{3})^2+(y-\stackrel{k}{2})^2=2^2~\hfill \stackrel{center}{(3,2)}

Check the picture below.

well, its radius didn't change, anyhow, you know what to check out.

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3 years ago
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