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tatyana61 [14]
3 years ago
5

Jonathan bought a table and some chairs at a furniture store. The equation that models this situation is y=25x+80, where y is th

e amount of money he spent and x is the number of chairs he bought.
What does the y-intercept mean in this solution?

A. He paid $25 for the table.
B. He paid $80 for the table.
C. He paid $25 for each chair.
D. He paid $80 for each chair.
Mathematics
2 answers:
Pachacha [2.7K]3 years ago
3 0
We have to look at what the y and x mean. X is the number of chairs while y is the amount of money. Since chairs cost $25, since the chairs is multiplied by it, the chairs have to be 80 since he only bought one table.
B. He paid $80 for the table.
Nimfa-mama [501]3 years ago
3 0
He paid 80 for the table give me the brainliest
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Answer:

a) Data given: 42 36 48 51 39 39 42 36 48 33 39 42 45

\bar X = 41.538

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b) 44.1, 37.8, 50.4, 53.55, 40.95, 44.1, 37.8, 50.4 ,34.65, 40.95, 44.1, 47.25

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\bar X= 3.462

s = 0.443

d) As we can see, the average of part b is 1.05 times the average of part a (1.05 * 41.538 = 43.615) and the average of part c is equal to the average obtained in part a divided by 12 (41.538 / 12 = 3.462).

And that happens because we create linear transformations for the parts b and c and the linear transformation affects the mean.

And you have the same interpretation for the deviation, it is affected by the linear transformation as the mean.

Step-by-step explanation:

For this case we can use the following formulas for the mean and standard deviation:

\bar X = \frac{\sum_{i=1}^n X_i}{n}

s = \sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}}

Part a

Data given: 42 36 48 51 39 39 42 36 48 33 39 42 45

And if we calculate the mean we got:

\bar X = 41.538

s = 5.317

Part b

For this case we know that each value present a 5% of rise so we just need to multiply each value bu 1.05 and we have this new dataset:

44.1, 37.8, 50.4, 53.55, 40.95, 44.1, 37.8, 50.4 ,34.65, 40.95, 44.1, 47.25

And if we calculate the new mean and deviation we got:

\bar X = 43.615

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Part c

The new dataset would be each value divided by 12 so we have:

3.5, 3, 4, 4.25, 3.25, 3.25, 3.5, 3, 4, 2.75, 3.25, 3.5, 3.75

And the new mean and deviation would be:

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Part d

As we can see, the average of part b is 1.05 times the average of part a (1.05 * 41.538 = 43.615) and the average of part c is equal to the average obtained in part a divided by 12 (41.538 / 12 = 3,462).

And that happens because we create linear transformations for the parts b and c and the linear transformation affects the mean.

And you have the same interpretation for the deviation, it is affected by the linear transformation as the mean.

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