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What is the volume of the sphere?

Ilia_Sergeevich [38]

Answer:

V = 4/3 pi or approximately 4.187 ft^3

Step-by-step explanation:

The volume of a sphere is given by

V = 4/3 pi r^3

The radius is 1 ft

V = 4/3 pi (1)^3

V = 4/3 pi

We can approximate pi by 3.14

V = 4/3 (3.14)

V = 4.186666666 ft^3

7 0

3 years ago

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A jewelry store sells necklaces in lengths that vary from 16 inches to 22 inches. Any necklaces outside of this criteria are rej

Art [367]

Answer:

16-22

Step-by-step explanation:

3 0

3 years ago

A scientist needs 15 liters of 25% acid solution for an experiment, but she only has a 10% solution and a 35% solution.How many

Artyom0805 [142]

By far fcurcutcugvpjvlg chi cig m

8 0

2 years ago

In a certain section of Southern California, the distribution of monthly rent for a one-bedroom apartment has a mean of $2,275 a

KATRIN_1 [288]

Answer:

100% probability of selecting a sample of 65 one-bedroom apartments and finding the mean to be at least $2,095 per month

Step-by-step explanation:

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

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, 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 $s = \frac{\sigma}{\sqrt{n}}$ .