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irga5000 [103]
3 years ago
7

Solve the system of equations. -10y+9x=-9 10y+5x=-5

Mathematics
1 answer:
alexira [117]3 years ago
3 0

by the use of elimination method

make all coefficients of subject to be eliminated similar..by multiplying the coefficients with one another

for eqn(i)

5(-10y+9x=-9)

-50y+45x=-45

for eqn(ii)

9(10y+5x=-5)

90y+45x=-45

-50y+45x=-45

90y+45x=-45

...subtract each set from the other...

we get

-140y+0=0

y=0

from eqn(i)

10y+5x=-5

0+5x=-5

x= -1

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Option 3 - 4 miles

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Given : In a city, the distance between the library and the police station is 3 miles less than twice the distance between the police  station and the fire station. The distance between the library and the police station is 5 miles.

To find : How far apart are the police  station and the fire station?

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Let the distance between police station and fire station be 'x'.

The distance between the library and the police station is 3 miles less than twice the distance between the police  station and the fire station.

i.e. 2x-3

The distance between the library and the police station is 5 miles.

i.e. 2x-3=5

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Therefore, The police and fire stations is 4 miles apart.

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Step-by-step explanation:

Since this question is lacking the matrix A, we will solve the question with the matrix

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so we can illustrate how to solve the problem step by step.

a) The characteristic polynomial is defined by the equation det(A-\lambdaI)=0 where I is the identity matrix of appropiate size and lambda is a variable to be solved. In our case,

\left|\left[\begin{matrix}4-\lamda & -2 \\ 1 & 1-\lambda \end{matrix}\right]\right|= 0 = (4-\lambda)(1-\lambda)+2 = \lambda^2-5\lambda+4+2 = \lambda^2-5\lambda+6

So the characteristic polynomial is \lambda^2-5\lambda+6=0.

b) The eigenvalues of the matrix are the roots of the characteristic polynomial. Note that

\lambda^2-5\lambda+6=(\lambda-3)(\lambda-2) =0

So \lambda=3, \lambda=2

c) To find the bases of each eigenspace, we replace the value of lambda and solve the homogeneus system(equalized to zero) of the resultant matrix. We will illustrate the process with one eigen value and the other one is left as an exercise.

If \lambda=3 we get the following matrix

\left[\begin{matrix}1 & -2 \\ 1 & -2 \end{matrix}\right].

Since both rows are equal, we have the equation

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For the case \lambda=2, using the same process, we get the vector (1,1).

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P=\left[\begin{matrix}2&1 \\ 1 & 1 \end{matrix}\right], D=\left[\begin{matrix}3&0 \\ 0 & 2 \end{matrix}\right]

This matrices are not unique, since they depend on the order in which we arrange the eigenvalues in the matrix D. Another pair or matrices that diagonalize A is

P=\left[\begin{matrix}1&2 \\ 1 & 1 \end{matrix}\right], D=\left[\begin{matrix}2&0 \\ 0 & 3 \end{matrix}\right]

which is obtained by interchanging the eigenvalues on the diagonal and their respective eigenvectors

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