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irinina [24]
3 years ago
8

One month Tammy rented 2 movies and 6 video games for a total of $ 42 . The next month she rented 5 movies and 3 video games for

a total of $ 30 . Find the rental cost for each movie and each video game.
Mathematics
1 answer:
EastWind [94]3 years ago
5 0

Answer:

The rental cost of one movie is $2.25 and the rental cost of one video game is $6.25

Step-by-step explanation:

Let the rental cost of 1 movie be m.

Let the rental cost of 1 video game be v.

One month, Tammy rented 2 movies and 6 video games for a total of $42. This means that:

2m + 6v = 42 ________ (1)

The next month she rented 5 movies and 3 video games for a total of $30. This means that:

5m + 3v = 30 _________(2)

We now have two simultaneous equations:

2m + 6v = 42 ________ (1)

5m + 3v = 30 _________(2)

Multiply (2) by 2, and we have:

2m + 6v = 42 __________ (1)

10m + 6v = 60 _________ (3)

Subtract (1) from (3):

 10m + 6v = 60

-<u> 2m + 6v = 42</u>

 <u>  8m     =     18</u>

=> m = 18 / 8

m = $2.25

Put the value of m back in (1):

2(2.25) + 6v = 42

4.5 + 6v = 42

=> 6v = 42 - 4.5 = 37.5

v = 37.5 / 6

v = $6.25

Therefore, the rental cost of one movie is $2.25 and the rental cost of one video game is $6.25

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An automobile dealer wants to see if there is a relationship between monthly sales and the interest rate. A random sample of 4 m
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Answer:

a) y=-6.254 x +75.064  

b) r =-0.932

The % of variation is given by the determination coefficient given by r^2 and on this case -0.932^2 =0.8687, so then the % of variation explained by the linear model is 86.87%.

Step-by-step explanation:

Assuming the following dataset:

Monthly Sales (Y)     Interest Rate (X)

       22                               9.2

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Part a

And we want a linear model on this way y=mx+b, where m represent the slope and b the intercept. In order to find the slope we have this formula:

m=\frac{S_{xy}}{S_{xx}}  

Where:  

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}  

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}  

With these we can find the sums:  

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=278.65-\frac{32.5^2}{4}=14.5875  

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i){n}}=696.9-\frac{32.5*97}{4}=-91.225  

And the slope would be:  

m=\frac{-91.225}{14.5875}=-6.254  

Nowe we can find the means for x and y like this:  

\bar x= \frac{\sum x_i}{n}=\frac{32.5}{4}=8.125  

\bar y= \frac{\sum y_i}{n}=\frac{97}{4}=24.25  

And we can find the intercept using this:  

b=\bar y -m \bar x=24.25-(-6.254*8.125)=75.064  

So the line would be given by:  

y=-6.254 x +75.064  

Part b

For this case we need to calculate the correlation coefficient given by:

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}  

r=\frac{4(696.9)-(32.5)(97)}{\sqrt{[4(278.65) -(32.5)^2][4(3009) -(97)^2]}}=-0.937  

So then the correlation coefficient would be r =-0.932

The % of variation is given by the determination coefficient given by r^2 and on this case -0.932^2 =0.8687, so then the % of variation explained by the linear model is 86.87%.

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Answer:

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__

Now we can write the two equations in the two unknowns:

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From the latter, we have ...

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Y is 479.17

7 0
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