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BigorU [14]
2 years ago
9

Ford Motor Company sells the Fusion SES for $24,400. The Fusion Hybrid sells for $29,975. What is the percentage increase in pri

ce for the Hybrid over the Fusion SES? (Round to tenth.)
Mathematics
2 answers:
Katyanochek1 [597]2 years ago
7 0

Answer:

The percentage increase in price for the Hybrid over the Fusion SES is of 22.84%, which means that the Hybrid is 22.84% more expensive that the Fusion SES.

Rounded to the nearest tenth, it is an increase of about 20%.

Step-by-step explanation:

Fusion SES has a value of $24,400, while the Fusion Hybrid has a value of $29,975. Therefore, the difference between both is of $5,575 (29,975 - 24,400 = 5,575).

In order to know the percentage increase in price for the Hybrid over the Fusion SES, we have to do the following calculation:

5,575 / 24,400 x 100 = Percentage increase in price

0,2284 x 100 = 22.84

The percentage increase in price for the Hybrid over the Fusion SES is of 22.84%, which means that the Hybrid is 22.84% more expensive that the Fusion SES.

Round to the nearest tenth, it is an increase of about 20%.

Lubov Fominskaja [6]2 years ago
6 0
Percent increase is:
Change/original * 100
(29975-24400)/24400
5575/24400= .228 * 100=
22.8%
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Answer:

a)Slope: \hat \beta_1 =\frac{7625.9}{1248.9}=6.106

Intercept: \hat \beta_o = 157.955 -6.106 (69.686)=-267.548

b) r=\frac{7625.9}{\sqrt{[1248.9][94228.8]}}=0.657  

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Step-by-step explanation:

Data given and definitions

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.  

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When we conduct a multiple regression we want to know about the relationship between several independent or predictor variables and a dependent or criterion variable.  

n=110, \sum x_i y_i = \sum (X-\bar X)(Y-\bar Y) =7625.9,\sum x^2_i=\sum (x-\bar x)^2 =1248.9 , sum y^2_i=\sum(y-\bar y)^2 =94228.8  

\sum Y_i =17375 , \sum X_i = 7665.5

Part a

The slope is given by this formula:

\hat \beta_1 =\frac{\sum (x-\bar x) (y-\bar y)}{\sum (x-\bar x )^2}

If we replace we got:

\hat \beta_1 =\frac{7625.9}{1248.9}=6.106

We can find the intercept with the following formula

\hat \beta_o = \bar y -\hat \beta_1 \bar x

We can find the average for x and y like this:

\bar X=7665.5/110 =69.686, \bar y= 17375/110=157.955

And replacing we got:

\hat \beta_o = 157.955 -6.106 (69.686)=-267.548

Part b

In order to calculate the correlation coefficient we can use this formula:  

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

For our case we have this:  

n=110, \sum x_i y_i = \sum (X-\bar X)(Y-\bar Y) =7625.9,\sum x^2_i=\sum (x-\bar x)^2 =1248.9 , sum y^2_i=\sum(y-\bar y)^2 =94228.8  

So we can find the correlation coefficient replacing like this:

r=\frac{7625.9}{\sqrt{[1248.9][94228.8]}}=0.657  

And the determination coeffecient is r^2 = 0.657^2 =0.432  

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