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Harrizon [31]
3 years ago
6

If you roll the six sided dice six times, are you guaranteed to get a sum of 7 once? answer

Mathematics
1 answer:
BlackZzzverrR [31]3 years ago
5 0
Yes it can be guaranteed to get a sum of 7 once
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You are comparing two refrigerator models. Their annual electricity consumption is shown below. Assume that the cost of electric
Otrada [13]

Answer:

Savings = $13

Step-by-step explanation:

$0.12 = 1 kilowatt-hour

So,

For Top-Freezer Refridgerator:

$0.12 × 529 = 1 × 529 kilowatt-hour

$63.48 = 529 kilowatt-hour

For Side-by-Side Refridgerator:

$0.12 × 634 = 1 × 634 kilowatt-hour

$76.08 = 634 kilowatt-hour

Savings = Side-by-Side Refridgerator - Top-

Freezer Refridgerator

Savings = $( 76.08 -63.48 )

Savings = $12.6

Savings = $13

5 0
3 years ago
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I will give brainiest to whoever answers correctly !!
Viktor [21]

Answer: 10k

Step-by-step explanation:

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3 years ago
Help me pliss <br>which one is correct?​
Anna71 [15]
D. (2,5) is the answer
4 0
2 years ago
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Solve the equation: only write the number is the box <br> 2( 5x+2)=54
Black_prince [1.1K]

Answer:

x = 5

Step-by-step explanation:

Step 1:

2 (5x + 2) = 54

Step 2:

10x + 4 = 54

Step 3:

10x = 50

Answer:

x = 5

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3 years ago
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Let e1= 1 0 and e2= 0 1 ​, y1= 4 5 ​, and y2= −2 7 ​, and let​ T: ℝ2→ℝ2 be a linear transformation that maps e1 into y1 and maps
Furkat [3]

Answer:

The image of \left[\begin{array}{c}4&-4\end{array}\right] through T is \left[\begin{array}{c}24&-8\end{array}\right]

Step-by-step explanation:

We know that T: IR^{2}  → IR^{2} is a linear transformation that maps e_{1} into y_{1} ⇒

T(e_{1})=y_{1}

And also maps e_{2} into y_{2}  ⇒

T(e_{2})=y_{2}

We need to find the image of the vector \left[\begin{array}{c}4&-4\end{array}\right]

We know that exists a matrix A from IR^{2x2} (because of how T was defined) such that :

T(x)=Ax for all x ∈ IR^{2}

We can find the matrix A by applying T to a base of the domain (IR^{2}).

Notice that we have that data :

B_{IR^{2}}= {e_{1},e_{2}}

Being B_{IR^{2}} the cannonic base of IR^{2}

The following step is to put the images from the vectors of the base into the columns of the new matrix A :

T(\left[\begin{array}{c}1&0\end{array}\right])=\left[\begin{array}{c}4&5\end{array}\right]   (Data of the problem)

T(\left[\begin{array}{c}0&1\end{array}\right])=\left[\begin{array}{c}-2&7\end{array}\right]   (Data of the problem)

Writing the matrix A :

A=\left[\begin{array}{cc}4&-2\\5&7\\\end{array}\right]

Now with the matrix A we can find the image of \left[\begin{array}{c}4&-4\\\end{array}\right] such as :

T(x)=Ax ⇒

T(\left[\begin{array}{c}4&-4\end{array}\right])=\left[\begin{array}{cc}4&-2\\5&7\\\end{array}\right]\left[\begin{array}{c}4&-4\end{array}\right]=\left[\begin{array}{c}24&-8\end{array}\right]

We found out that the image of \left[\begin{array}{c}4&-4\end{array}\right] through T is the vector \left[\begin{array}{c}24&-8\end{array}\right]

3 0
3 years ago
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