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Veseljchak [2.6K]
3 years ago
11

A salesperson makes 18% commission on every TV sold. If the salesperson sold four TV’s at $885 each, how much commission did the

y make?
Mathematics
1 answer:
Levart [38]3 years ago
5 0

Answer:

They made a $531 commission.

Step-by-step explanation:

The given is:

  • The price of each TV is $885
  • The commission is 18% on every TV sold
  • The salesperson sold 4 TV's

We need the value of the commission

Let us find the commission of every TV, then find the total amount of all

∵ The price of each TV is $885

∵ The commission is 18 %

→ Find 18% of $885

∴ The commission on every TV = 885 × 15%

∴ The commission on every TV = 885 × 15/100

∴ The commission on every TV = $132.75

∵ The salesperson sold 4 TV

∴ The commission on them = 4 × 132.75

∴ The commission on them = $531

They made a $531 commission.

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Answer:

\frac{x-2}{x+3}

Step-by-step explanation:

given \frac{(x-3)(x-2)}{(x+3)(x-3)}

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\frac{x-2}{x+3}


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According to a report from a business intelligence company, smartphone owners are using an average of 22 apps per month. Assume
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Answer:

0.4332 = 43.32% probability that the sample mean is between 21 and 22.

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 establishes 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.

According to a report from a business intelligence company, smartphone owners are using an average of 22 apps per month.

This means that \mu = 22

Standard deviation is 4:

This means that \sigma = 4

Sample of 36:

This means that n = 36, s = \frac{4}{sqrt{36}}

What is the probability that the sample mean is between 21 and 22?

This is the p-value of Z when X = 22 subtracted by the p-value of Z when X = 21.

X = 22

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

By the Central Limit Theorem

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

Z = \frac{22 - 22}{\frac{4}{sqrt{36}}}

Z = 0

Z = 0 has a p-value of 0.5.

X = 21

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

Z = \frac{21 - 22}{\frac{4}{sqrt{36}}}

Z = -1.5

Z = -1.5 has a p-value of 0.0668.

0.5 - 0.0668 = 0.4332

0.4332 = 43.32% probability that the sample mean is between 21 and 22.

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