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Dmitry [639]
4 years ago
5

Solve for x

3(x + 1) = 5(x - 2) + 7" alt="3(x + 1) = 5(x - 2) + 7" align="absmiddle" class="latex-formula">
Mathematics
2 answers:
Paul [167]4 years ago
4 0

3(x + 1) = 5(x - 2) + 7

  • Distribute 3 and 5 inside their respective parentheses.

3x + 3 = 5x - 10 + 7

  • Combine like terms.

3x + 3 = 5x - 3

  • Add 3 to both sides.

3x + 6 = 5x

  • Subtract 3x from both sides.

6 = 2x

  • Divide both sides by 2.
<h3>x = 3</h3>
patriot [66]4 years ago
3 0

3(x+1)=5(x-2)+7\\\\&#10;3x+3=5x-10+7\\\\&#10;2x=6\\\\&#10;x=3

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The cost of goods sold is $10,258 million and the Cash paid to supplier is $10,447 million.

<h3>Cost of goods sold</h3>

a. Cost of goods sold

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Cost of goods sold = $1,997 + $10,392 - $2,131

Cost of goods sold = $10,258

b. Cash paid to supplier

Cash paid=2015 Beginning balance  + Purchases - 2015 Ending balance

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2 years ago
A company produces steel rods. The lengths of the steel rods are normally distributed with a mean of 111.4-cm and a standard dev
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Answer:

P(111.2-cm < ¯ x < 111.4-cm) = 0.4726

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.

In this problem, we have that:

\mu = 111.4, \sigma = 0.5, n = 23, s = \frac{0.5}{\sqrt{23}} = 0.1043

Find the probability that the average length of a randomly selected bundle of steel rods is between 111.2-cm and 111.4-cm.

This is the pvalue of Z when X = 111.4 subtracted by the pvalue of Z when X = 111.2. So

X = 111.4

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

By the Central Limit Theorem

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

Z = \frac{111.4 - 111.4}{0.1043}

Z = 0

Z = 0 has a pvalue of 0.5.

X = 111.2

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

Z = \frac{111.2 - 111.4}{0.1043}

Z = -1.92

Z = -1.92 has a pvalue of 0.0274.

0.5 - 0.0274 = 0.4726

P(111.2-cm < ¯ x < 111.4-cm) = 0.4726

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