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mihalych1998 [28]
3 years ago
12

The YMCA lap pool is a right rectangular prism

Mathematics
2 answers:
serg [7]3 years ago
7 0

Answer:

<u>2 Meters deep.</u>

Step-by-step explanation:

If you multiply 36.8 m by 20m, you would get the base area of 736 m^2. If you divide that by 1472, you would get 2 meters deep.

Rasek [7]3 years ago
6 0

To find the depth (aka "height") you must use the volume formula

Volume = length x width x height

In this case:

The amount of water the pool can contain will equal to the volume

Volume = 1,472 m

length =  36.8 m

width = 20 m

height = unknown (let's make this h)

^^^Plug these numbers into the formula given above

1,472 = 36.8 x 20 x h

1,472 = 736h

Isolate h by dividing 736 to both sides

1,472/736 = 736h/736

2

This pool is 2 meters deep

Hope this helped!

~Just a girl in love with Shawn Mendes

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The average amount of water in randomly selected 16-ounce bottles of water is 16.15 ounces with a standard deviation of 0.45 oun
vekshin1

Answer:

0.0179 = 1.79% probability that the mean of this sample is less than 15.99 ounces of water.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this question, we have that:

\mu = 16.15, \sigma = 0.45, n = 35, s = \frac{0.45}{\sqrt{35}} = 0.0761

What is the probability that the mean of this sample is less than 15.99 ounces of water?

This is the pvalue of Z when X = 15.99. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{15.99 - 16.15}{0.0761}

Z = -2.1

Z = -2.1 has a pvalue of 0.0179

0.0179 = 1.79% probability that the mean of this sample is less than 15.99 ounces of water.

3 0
3 years ago
Graph the equation
Lisa [10]
To find the root, replace y with 0
X^2-12x+35=0
A=1 B=-12 C=35
B^2-4ac=(-12)^2 -4(1)(35)
=144 -140
=4


x=(-b+/- square root of b^2 -4ac) /over/ (2a)
Plug in the numbers
x=-(-12) sqr (-12)^2 4(1)(35) / (2)(1)
X=12 +/-sqr 4 / 2
Positive outcome
x=12 + sqr 4 / 2
x=12+2/2
x=7 <— this one
Negative outcome
x=12-2i/2
x=6-i
Vertex: (6,-1)
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Step-by-step explanation:

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4 0
3 years ago
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