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Vladimir [108]
4 years ago
8

the amount y of your friends allowances if the amount she receives is 2$ more than the amount x you receive

Mathematics
1 answer:
liberstina [14]4 years ago
7 0

Hello, How are you doing today?

If your friend makes 2$ more than you do, then you must form an equation for the problem. y = amount she has, x = your amount. Therefor, it would be:

y = x + 2

If you make 6 dollars, she will make 8 and so on. Thank you, have a nice day!

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Reuben bought 5CDS that were each the same priceIncluding sales tax, he paid a total of \$81.50. Each CD had a tax of $0.60. wha
Liula [17]

Answer:

The price of each CD before tax is $15.70

Step-by-step explanation:

Given that:

Number of CDs bought by Reuben = 5

Cost of five CDs = $81.50

Sales tax on each CD = $0.60

Sales tax on 5 CDs = 0.60*5 = $3.00

Price of CDs without tax = 81.50 - 3.00 = $78.50

Price of each CD = \frac{Cost\ of\ CDs}{No.\ of\ CDs}

Price of each CD = \frac{78.50}{5}

Price of each CD = $15.70

Hence,

The price of each CD before sales tax is $15.70

7 0
3 years ago
Help please <3 <3 <3
fomenos

Answer:

A group of ten people would be willing to spend 135$

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Step-by-step explanation:

4 0
3 years ago
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Round 8.923 to the nearest half.
Furkat [3]

Answer:

8.923 to the nearest half is 8.9

Step-by-step explanation:

6 0
3 years ago
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Tom wants to order tickets online so that he and three of his friends can go together to a water park. The cost of the tickets i
iVinArrow [24]

Answer:

Expression is:16n+2.50

For buying 4 tickets: 66.50

Step-by-step explanation:

You first have to set up the equation and each ticket cost 16 and you have to buy sixteen that is why it is 16n and then you have to pay 2.50 because you are buying online. Then you put four in for N because you are getting 4 tickets. Finally multiply 16 and 4 then add 2.50.


7 0
3 years ago
Let A be a given matrix below. First, find the eigenvalues and their corresponding eigenspaces for the following matrices. Then,
Rama09 [41]

It looks like given matrices are supposed to be

\begin{array}{ccccccc}\begin{bmatrix}3&2\\2&3\end{bmatrix} & & \begin{bmatrix}1&-1\\2&-1\end{bmatrix} & & \begin{bmatrix}1&2&3\\0&2&3\\0&0&3\end{bmatrix} & & \begin{bmatrix}3&1&1\\1&3&1\\1&1&3\end{bmatrix}\end{array}

You can find the eigenvalues of matrix A by solving for λ in the equation det(A - λI) = 0, where I is the identity matrix. We also have the following facts about eigenvalues:

• tr(A) = trace of A = sum of diagonal entries = sum of eigenvalues

• det(A) = determinant of A = product of eigenvalues

(a) The eigenvalues are λ₁ = 1 and λ₂ = 5, since

\mathrm{tr}\begin{bmatrix}3&2\\2&3\end{bmatrix} = 3 + 3 = 6

\det\begin{bmatrix}3&2\\2&3\end{bmatrix} = 3^2-2^2 = 5

and

λ₁ + λ₂ = 6   ⇒   λ₁ λ₂ = λ₁ (6 - λ₁) = 5

⇒   6 λ₁ - λ₁² = 5

⇒   λ₁² - 6 λ₁ + 5 = 0

⇒   (λ₁ - 5) (λ₁ - 1) = 0

⇒   λ₁ = 5 or λ₁ = 1

To find the corresponding eigenvectors, we solve for the vector v in Av = λv, or equivalently (A - λI) v = 0.

• For λ = 1, we have

\begin{bmatrix}3-1&2\\2&3-1\end{bmatrix}v = \begin{bmatrix}2&2\\2&2\end{bmatrix}v = 0

With v = (v₁, v₂)ᵀ, this equation tells us that

2 v₁ + 2 v₂ = 0

so that if we choose v₁ = -1, then v₂ = 1. So Av = v for the eigenvector v = (-1, 1)ᵀ.

• For λ = 5, we would end up with

\begin{bmatrix}-2&2\\2&-2\end{bmatrix}v = 0

and this tells us

-2 v₁ + 2 v₂ = 0

and it follows that v = (1, 1)ᵀ.

Then the decomposition of A into PDP⁻¹ is obtained with

P = \begin{bmatrix}-1 & 1 \\ 1 & 1\end{bmatrix}

D = \begin{bmatrix}1 & 0 \\ 0 & 5\end{bmatrix}

where the n-th column of P is the eigenvector associated with the eigenvalue in the n-th row/column of D.

(b) Consult part (a) for specific details. You would find that the eigenvalues are i and -i, as in i = √(-1). The corresponding eigenvectors are (1 + i, 2)ᵀ and (1 - i, 2)ᵀ, so that A = PDP⁻¹ if

P = \begin{bmatrix}1+i & 1-i\\2&2\end{bmatrix}

D = \begin{bmatrix}i&0\\0&i\end{bmatrix}

(c) For a 3×3 matrix, I'm not aware of any shortcuts like above, so we proceed as usual:

\det(A-\lambda I) = \det\begin{bmatrix}1-\lambda & 2 & 3 \\ 0 & 2-\lambda & 3 \\ 0 & 0 & 3-\lambda\end{bmatrix} = 0

Since A - λI is upper-triangular, the determinant is exactly the product the entries on the diagonal:

det(A - λI) = (1 - λ) (2 - λ) (3 - λ) = 0

and it follows that the eigenvalues are λ₁ = 1, λ₂ = 2, and λ₃ = 3. Now solve for v = (v₁, v₂, v₃)ᵀ such that (A - λI) v = 0.

• For λ = 1,

\begin{bmatrix}0&2&3\\0&1&3\\0&0&2\end{bmatrix}v = 0

tells us we can freely choose v₁ = 1, while the other components must be v₂ = v₃ = 0. Then v = (1, 0, 0)ᵀ.

• For λ = 2,

\begin{bmatrix}-1&2&3\\0&0&3\\0&0&1\end{bmatrix}v = 0

tells us we need to fix v₃ = 0. Then -v₁ + 2 v₂ = 0, so we can choose, say, v₂ = 1 and v₁ = 2. Then v = (2, 1, 0)ᵀ.

• For λ = 3,

\begin{bmatrix}-2&2&3\\0&-1&3\\0&0&0\end{bmatrix}v = 0

tells us if we choose v₃ = 1, then it follows that v₂ = 3 and v₁ = 9/2. To make things neater, let's scale these components by a factor of 2, so that v = (9, 6, 2)ᵀ.

Then we have A = PDP⁻¹ for

P = \begin{bmatrix}1&2&9\\0&1&6\\0&0&2\end{bmatrix}

D = \begin{bmatrix}1&0&0\\0&2&0\\0&0&3\end{bmatrix}

(d) Consult part (c) for all the details. Or, we can observe that λ₁ = 2 is an eigenvalue, since subtracting 2I from A gives a matrix of only 1s and det(A - 2I) = 0. Then using the eigen-facts,

• tr(A) = 3 + 3 + 3 = 9 = 2 + λ₂ + λ₃   ⇒   λ₂ + λ₃ = 7

• det(A) = 20 = 2 λ₂ λ₃   ⇒   λ₂ λ₃ = 10

and we find λ₂ = 2 and λ₃ = 5.

I'll omit the details for finding the eigenvector associated with λ = 5; I ended up with v = (1, 1, 1)ᵀ.

• For λ = 2,

\begin{bmatrix}1&1&1\\1&1&1\\1&1&1\end{bmatrix}v = 0

tells us that if we fix v₃ = 0, then v₁ + v₂ = 0, so that we can pick v₁ = 1 and v₂ = -1. So v = (1, -1, 0)ᵀ.

• For the repeated eigenvalue λ = 2, we find the generalized eigenvector such that (A - 2I)² v = 0.

\begin{bmatrix}1&1&1\\1&1&1\\1&1&1\end{bmatrix}^2 v = \begin{bmatrix}3&3&3\\3&3&3\\3&3&3\end{bmatrix}v = 0

This time we fix v₂ = 0, so that 3 v₁ + 3 v₃ = 0, and we can pick v₁ = 1 and v₃ = -1. So v = (1, 0, -1)ᵀ.

Then A = PDP⁻¹ if

P = \begin{bmatrix}1 & 1 & 1 \\ 1 & -1 & 0 \\ 1 & 0 & -1\end{bmatrix}

D = \begin{bmatrix}5&0&0\\0&2&0\\0&2&2\end{bmatrix}

3 0
3 years ago
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