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Ipatiy
3 months ago
14

B = 3 V/H solve for V

Mathematics
2 answers:
PIT_PIT [12.4K]3 months ago
7 0
<span>B = 3V/H, Find V:)

To isolate V, we will eliminate the fractions.

Multiply both sides by H.

H × B = 3V/H × H

This simplifies to:

BH = 3V

Now, divide both sides by 3 to isolate V.

BH ÷ 3 = 3V ÷ 3

Thus we find:

1/3BH = V

So, V = 1/3BH

~I hope this is helpful!~


</span>
PIT_PIT [12.4K]3 months ago
5 0
<span>B=(3v)/(h)

To isolate v, we need to rearrange the equation.
Move v to the left side.
(3v)/(h)=B

Next, multiply the entire equation by h.
(3v)/(h)*h=B*h

Now cancel the common factors on the left side.
3v=B*h

Multiply B by h to yield hB.
3v=hB

Divide each side by 3 to get v alone.
(3v)/(3)=(hB)/(3)

Then simplify again.
v=(hB)/(3)
============
You can try different values...
8=(3v)/(3)

Rearranging the equation to place v on the left side gives us:
(3v)/(3)=8

Now, multiply each term by 3.
(3v)/(3)*3=8*3

This results in:
3v=8*3

Calculating gives us 24.
3v=24

To isolate v, divide by 3.
(3v)/(3)=(24)/(3)

Left side is simplified to:
v=(24)/(3) </span>
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The inside diameter of a randomly selected piston ring is a random variable with mean value 13 cm and standard deviation 0.08 cm
Zina [12379]

Answer:

(a) P(12.99 ≤ X ≤ 13.01) = 0.3840

(b) P(X ≥ 13.01) = 0.3075

Step-by-step explanation:

To address this problem, one needs to grasp the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems involving normally distributed samples are resolved through the application of the z-score formula.

In a data set with a mean \mu and standard deviation \sigma, the z-score for a measurement X is defined as:

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

The Z-score indicates how many standard deviations the measurement deviates from the mean. After determining the Z-score, one can consult the z-score table to find the relevant p-value for that score. This p-value represents the probability that the measure's value is less than X, which indicates the percentile of X. By subtracting this p-value from 1, we obtain the likelihood that the measure's value exceeds X.

Central Limit Theorem

According to the Central Limit Theorem, 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 by a normal distribution, characterized by mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

The Central Limit Theorem can also be applicable to a skewed variable, provided that n is 30 or more.

In this case, we are given that:

\mu = 13, \sigma = 0.08

(a) Compute P(12.99 ≤ X ≤ 13.01) when n = 16.

In this scenario, we find n = 16, s = \frac{0.08}{\sqrt{16}} = 0.02

This probability equates to the p-value of Z at X = 13.01 minus the p-value of Z at X = 12.99.

X = 13.01

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

According to the Central Limit Theorem

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

Z = \frac{13.01 - 13}{0.02}

Z = 0.5

has a p-value of 0.6915

Z = 0.5

X = 12.99

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

Z = \frac{12.99 - 13}{0.02}

Z = -0.5

Z = -0.5 yields a p-value of 0.3075

0.6915 - 0.3075 = 0.3840

P(12.99 ≤ X ≤ 13.01) = 0.3840

(b) What is the probability that the sample mean diameter is greater than 13.01 when n = 25?

P(X ≥ 13.01) =

This is obtained by subtracting the p-value of Z when X = 13.01 from 1. Hence

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

Z = \frac{13.01 - 13}{0.02}

Z = 0.5

Z = 0.5 has a p-value of 0.6915

1 - 0.6915 = 0.3075

P(X ≥ 13.01) = 0.3075

7 0
2 months ago
Read 2 more answers
Earyn owns French Twist Hair Salon. She charges $35 for a cut an $120 for a cut and color combo. Yesterday she had seven clients
Leona [12618]
35x + 120y = 500
I hope this makes sense
6 0
2 months ago
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