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yawa3891 [41]
3 years ago
13

A motorboat can maintain a constant speed of 17 miles

Mathematics
1 answer:
maxonik [38]3 years ago
6 0

Answer:

10mph

Step-by-step explanation:

by adding total time taken to travel and return and simply doing math

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22 divided by 2,739 with the quotient and remainder
Margaret [11]

Answer:

124.5

Step-by-step explanation:

3 0
4 years ago
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HELP! Which of the following pairs of functions are inverses of each other?
IrinaK [193]

one way is to solve for the invers of the first function

remembe, to solve, replace f(x) or g(x) with y, switch x and y, solve for y and replace it with f⁻¹(x)


A.

f(x)=x/2+8

y=x/2+8

x=y/2+8

x-8=y/2

2x-16=y

f⁻¹(x)=2x-16

nope, not A



B.

f(x)=3x³+16

y=3x³+16

x=3y³+16

x-16=3y³

(x-16)/3=y³

∛((x-16)/3)=y

f⁻¹(x)=∛((x-16)/3)

nope, not the same

not B


C.

f(x)=18/x-9

y=18/x-9

x=18/y-9

x+9=18/y

y(x+9)=18

y=18/(x+9)

f⁻¹(x)=18/(x+9)

correct, the answer is C




answer is C



8 0
3 years ago
Read 2 more answers
Eva bought a guitar for $80. Later that guitar was marked down by 35%. By how much has the value been decreased?
Orlov [11]

Answer:

r

Step-by-step explanation:

3 0
3 years ago
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This set of ordered pairs shows a relationship between x and y. {(0, -2), (3, 7), (6, 16), (6, 15), (8, 21), (10, 28), (11,31)}
Hunter-Best [27]

Answer:

The closest to the output when the input is approximately 12

Step-by-step explanation:

The given (x, y) coordinates are;

The line of best fit is

x, 0, 3, 6, 6, 8, 10, 11

y, -2, 7, 16, 15, 21, 28, 31

The line of best fit can be obtained from the scatter plot of the given data from where a linear pattern is apparent

A linear line of best fit is a trend line that gives an overall cumulative minimum distance of all the points from the line

The method for constructing a line of best fit includes;

1) The least Squares Method

2) The method of linear regression

3) Construction of line of best fit

a) The area method

b) The dividing method

The least squares equation is given as follows;

\hat y = a + b·x

b = \dfrac{\Sigma (x_i - \overline x) \cdot (y_i - \overline y)}{\Sigma (x_i - \overline x)^2 }

From MS Excel, we have;

{\Sigma (x_i - \overline x) \cdot (y_i - \overline y)}{ } = 266.8571

{\Sigma (x_i - \overline x)^2 } = 89.42857

∴ b = 266.8571/89.42857 ≈ 2.984

a =\overline y- b \cdot \overline x

From MS Excel, with the given data, we get;

\overline y = 16.57143

\overline x = 6.285714

Therefore;

a = 16.57143 - 2.984 × 6.285714 = -2.185

Therefore, we get the following regression equation;

\hat y = -2.185 + 2.9·x

Where;

x = The input

\hat y = The output

Therefore, when x = 5, we get;

\hat y = -2.185 + 2.9 × 5 = 12.315

Therefore, the closest to the output when the input is 5, y ≈ 12

8 0
3 years ago
I just need the answer to this
nataly862011 [7]

Answer:

Step-by-step explanation:

angle 6

5 0
3 years ago
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