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maw [93]
3 years ago
9

Please answer 14 and 13

Mathematics
2 answers:
Colt1911 [192]3 years ago
7 0
7/4 * 301/2 (changed into mixed numbers)
2107/8
263.375
C
because when you change 3 into a mixed fraction its 263*8+3/8
263.375
#1
sasho [114]3 years ago
7 0
13: I would convert 1 3/4 to 1.75 percent. Then, change 150 1/2 to 150.50. Multiply those:
150.50
x 1.75
263.375. Convert that into a fraction which equals 263 3/8, making the answer (C), 263 3/8.
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Which equation is equivalent to log (x+5) = 27
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Answer:

(22+5)=27 or  (x+y)=27

Step-by-step explanation:

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The mean annual income for people in a certain city is 37 thousand dollars, with a standard deviation of 28 thousand dollars. A
Aloiza [94]

Answer:

P( 31 < \bar X< 41)

And we can ue the z score formula given by:

z= \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And using this formula we got for the limits:

z = \frac{31-37}{\frac{28}{\sqrt{50}}}= -1.515

z = \frac{41-37}{\frac{28}{\sqrt{50}}}= 1.01

So we want to find this probability:

P(-1.515

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution to the problem

Let X the random variable that represent the annual income of a population, and for this case we know the following info:

\mu=37 and \sigma=28  and we are omitting the zeros from the thousand to simplify calculations

We select a sample size of n=50>30.

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

From the central limit theorem we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

And we want to find this probability:

P( 31 < \bar X< 41)

And we can ue the z score formula given by:

z= \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And using this formula we got for the limits:

z = \frac{31-37}{\frac{28}{\sqrt{50}}}= -1.515

z = \frac{41-37}{\frac{28}{\sqrt{50}}}= 1.01

So we want to find this probability:

P(-1.515

4 0
3 years ago
How do i complete this with quadratics?
Bond [772]
I hope this helps you



log6 [x. (2x-7)]=log6 (6^2)


x. (2x-7)=36



2x^2-14x-36=0

2x +4



x -9


(2x+4)(x-9)=0


x= -2


x=9





7 0
3 years ago
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