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zubka84 [21]
3 years ago
14

The circumference of the base of the cone is 8.5π inches. What is the volume of the cone in terms of π? Round to the nearest hun

dredth. Enter your answer in the box.

Mathematics
1 answer:
Contact [7]3 years ago
4 0

Answer:

The volume of the cone in terms of π is 90.31π inches³ to the nearest hundredth.

Step-by-step explanation:

Volume = πr²(h/3) = ?

          Height = <em>15 inches</em> (from the diagram)

          Find r

since we are given the circumference of the base circle = 8.5π inches => 2πr

∴ 8.5π inches = 2πr

  ( 8.5π / 2π ) inches = r

  <em>4.25 inches</em> = (r) Radius

Now that we have both Height (15 inches) and Radius (4.25 inches), calculate the volume.

Volume = πr²(h/3)

             = π * (4.25 inches)² * (15 inches / 3)

             = π * 18.0625 inches² * 5 inches

Volume = ‬90.3125π inches³

Rounding to the nearest hundredth ≅ 90.31π inches³

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8.5x10000-3.0x10^3

Simplify 8.5x*10000 to 85000x
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4.8 + 2.2w − 1.4w + 2.4 ?
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Step-by-step explanation:

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The inside diameter of a randomly selected piston ring is a random variable with mean value 8 cm and standard deviation 0.03 cm.
S_A_V [24]

Answer:

a) P(7.99 ≤ X ≤ 8.01) = 0.8164

b) P(X ≥ 8.01) = 0.0475.

Step-by-step explanation:

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

Normal probability distribution:

Problems of normally distributed samples can be solved using 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 random variable X, with mean \mu and standard deviation \sigma, the sample means with size n can be approximated to a normal distribution with mean

In this problem, we have that:

\mu = 8, \sigma = 0.03

(a) Calculate P(7.99 ≤ X ≤ 8.01) when n = 16.

n = 16, so s = \frac{0.03}{4} = 0.0075

This probability is the pvalue of Z when X = 8.01 subtracted by the pvalue of Z when X = 7.99. So

X = 8.01

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

Applying the Central Limit Theorem

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

Z = \frac{8.01 - 8}{0.0075}

Z = 1.33

Z = 1.33 has a pvalue of 0.9082

X = 7.99

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

Z = \frac{7.99 - 8}{0.0075}

Z = -1.33

Z = -1.33 has a pvalue of 0.0918

0.9082 - 0.0918 = 0.8164

P(7.99 ≤ X ≤ 8.01) = 0.8164

(b) How likely is it that the sample mean diameter exceeds 8.01 when n = 25? P(X ≥ 8.01) =

n = 25, so s = \frac{0.03}{5} = 0.006

This is 1 subtracted by the pvalue of Z when X = 8.01. So

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

Z = \frac{8.01 - 8}{0.006}

Z = 1.67

Z = 1.67 has a pvalue of 0.9525

1 - 0.9525 = 0.0475

P(X ≥ 8.01) = 0.0475.

4 0
3 years ago
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