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vichka [17]
2 years ago
10

13 - [(3² x 4) - 30]

Mathematics
2 answers:
natali 33 [55]2 years ago
6 0

Answer:

7

Step-by-step explanation:

I think the answer you're looking for is 7

NemiM [27]2 years ago
3 0

Answer:

7

Step-by-step explanation:

13 - [(3² x 4) - 30]

13 - [(9 x 4) - 30]

13 - (36 - 30)

13-6

7

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Step-by-step explanation:

12\sqrt{11}=\sqrt{11*12*12}\\\\=\sqrt{1584}

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I need to know how to get the scale factor from a h-shaped polygon
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Alex plotted 3 points of a rectangle on a coordinate plane at (-2,3),(4,3) and (-2,-1). What is the 4th point of the rectangle
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(4,-1)

These are the only numbers that weren’t repeated yet.
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An exterior angle of an isosceles triangle has measure 150°. Find two possible sets of measures for the angles of the triangle.
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If the exterior angle of the bases is 150°​, then the measure of the angle of each base is
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5 0
3 years ago
A researcher believes that 9% of females smoke cigarettes. If the researcher is correct, what is the probability that the propor
lara31 [8.8K]

Answer:

The probability that the sample proportion would differ from the population proportion by more than 3% is 0.0027.

Step-by-step explanation:

Let <em>X</em> = number of females who smoke cigarettes.

The probability that a female smoke cigarettes is, <em>p</em> = 0.09.

A random sample of size, <em>n</em> = 703 females were selected to determine the sample proportion of females who smoke cigarettes.

A female smoking cigarettes is independent from others.

The random variable <em>X</em> follows a Binomial distribution with parameters <em>n</em> = 703 and <em>p</em> = 0.09.

Now, as the sample size is quite large, i.e. <em>n</em> = 703 > 30, according to the Central limit theorem the sampling distribution of sample proportion can be described by the Normal distribution.

The mean of this sampling distribution is same as the population proportion, i.e. \mu_{\hat p}=p=0.09.

And the standard deviation of the sampling distribution of sample proportion is:

\sigma_{\hat p}=\sqrt{\frac{p(1-p)}{n}}=\sqrt{\frac{0.09(1-0.09)}{703}}=0.0108

Compute the probability that the sample proportion would differ from the population proportion by more than 3% as follows:

\hat p-p>0.03\\\hat p>0.03+p\\\hat p>0.03+0.09\\\hat p>0.12

Compute the value of P(\hat p>0.12) as follows:

P(\hat p>0.12)=P(\frac{\hat p-p}{\sigma_{\hat p}}>\frac{0.03}{0.0108})\\=P(Z>2.78)\\=1-P(Z

Thus, the probability that the sample proportion would differ from the population proportion by more than 3% is 0.0027.

7 0
3 years ago
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