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vfiekz [6]
2 years ago
10

1. What is the volume for the following rectangular prism?

Mathematics
1 answer:
____ [38]2 years ago
8 0

Answer:

2. c) 1050 mm³

3. c) 8 yards.

Step-by-step explanation:

Given the following data;

Length = 25mm

Width = 7 mm

Height = 6 mm

To find the volume of the rectangular prism;

Volume of rectangular prism = base area * height

First of all, we would determine the base area;

Base area = length * width

Base area = 25 * 7

Base area = 175 mm²

Next, we find the volume;

Volume of rectangular prism = 175 * 6

Volume of rectangular prism = 1050 mm³

Question 2.

Given the following data;

Length = 9 yards

Width = 7.5 yards

Volume = 540 cubic yards

To find the height of the rectangular prism, x;

Volume of rectangular prism = length * width * height

540 = 9 * 7.5 * x

540 = 67.5x

x = 540/67.5

Height, x = 8 yards

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A Government company claims that an average light bulb lasts 270 days. A researcher randomly selects 18 bulbs for testing. The s
Fofino [41]

Answer:

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

In this question, we have that:

\mu = 270, \sigma = 90, n = 18, s = \frac{90}{\sqrt{18}} = 21.2

What is the probability that 18 randomly selected bulbs would have an average life of no more than 260 days?

This is the pvalue of Z when X = 260. So

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

By the Central Limit Theorem

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

Z = \frac{260 - 270}{21.2}

Z = -0.47

Z = -0.47 has a pvalue of 0.3192.

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

5 0
3 years ago
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