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Anni [7]
3 years ago
7

My teacher never explained how to do this so can someone help me?

Mathematics
1 answer:
Natalka [10]3 years ago
6 0

Answer:

75cm^2

Step-by-step explanation:

When you say a rectangular prism, it means it has the base has 4 sides of which opposite sides are equal as a rectangle. This sides substends so we have a total of 6 surfaces in this prism.

This 6 surfaces has 3 surface area the same.

The surface area = sum of area of all faces.

325= 50 + 50 + 37.5 + 37.5 + 2x; where X is the area of the surface unknown.

325= 100+ 75 + 2x

325-175= 150

150= 2x

X= 150/ 2 = 75 cm^2

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3 years ago
A store owner makes a profit of $54 when he sells 9 jackets.How many jackets should he sell to make a profit of $270? jackets
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4 years ago
Mrs. Martinez teaches Spanish part time at a nearby college. In one class, there are 12 women and 14 men; in her other class, th
AleksandrR [38]

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Step-by-step explanation:

7 0
3 years ago
Data from the Centers for Disease Control and Prevention indicate that weights of American adults in 2005 had a mean of 167 poun
sesenic [268]

Answer:

92.65% probability that the total weight in a random sample of 47 American adults exceeds 7500 pounds in 2005.

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 normally distributed samples are 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 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 sums the theorem can also be used, with mean n*\mu and standard deviation s = \sqrt{n}*\sigma

In this problem, we have that:

n = 47, \mu = 47*167 = 7849, s = \sqrt{47}*35 = 240

Use this information to estimate the probability that the total weight in a random sample of 47 American adults exceeds 7500 pounds in 2005.

This is 1 subtracted by the pvalue of Z when X = 7500. So

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

By the Central Limit Theorem

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

Z = \frac{7500 - 7849}{240}

Z = -1.45

Z = -1.45 has a pvalue of 0.0735

1 - 0.0735 = 0.9265

92.65% probability that the total weight in a random sample of 47 American adults exceeds 7500 pounds in 2005.

5 0
3 years ago
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