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AnnZ [28]
4 years ago
11

Madison works as a salesperson at an electronics store and sells phones and phone accessories, and makes a fixed commission for

each phone sale and a different fixed commission for each accessory sale. Yesterday Madison sold 8 phones and 10 accessories and made a total commission of $107. Today she sold 4 phones and 23 accessories and made a total commission of $116.50. Determine the price of each phone and the price of each accessory.
Mathematics
1 answer:
Jet001 [13]4 years ago
4 0

Answer:

Price of each phone: \$9

Price of each accessory: \$3.5

Step-by-step explanation:

Let be "p" the  price in dollars of each phone and "a" the price in dollars of each accessory.

Set up a system of equations:

\left \{ {{8p+10a=107} \atop {4p+23a=116.50}} \right.

You can use the Elimination Method to solve the system.

Multiply the second equation by -2 and add both equations:

\left \{ {{8p+10a=107} \atop {-8p-46a=-233}} \right.\\............................\\-36a=-126\\\\a=\frac{-126}{-36}\\\\a=3.5

Substitute the value of "a" into the first equation and solve for "p":

8p+10(3.5)=107\\\\8p=107-35\\\\p=\frac{72}{8}\\\\p=9

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Angle RST below is a right angle. What is the measure, in degrees, of
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Answer:

RSM = 56.4

Step-by-step explanation:

RSM + MST = RST

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The mean rent of a 3-bedroom apartment in Orlando is $1300. You randomly select 10 apartments around town. The rents are normall
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Answer:

96.49% probability that the mean rent is more than $1100

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 = 1300, \sigma = 350, n = 10, s = \frac{350}{\sqrt{10}} = 110.68

What is the probability that the mean rent is more than $1100?

This is 1 subtracted by the pvalue of Z when X = 1100. So

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

By the Central Limit Theorem

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

Z = \frac{1100 - 1300}{110.68}

Z = -1.81

Z = -1.81 has a pvalue of 0.0351

1 - 0.0351 = 0.9649

96.49% probability that the mean rent is more than $1100

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Step-by-step explanation:

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