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pashok25 [27]
3 years ago
5

What reflection of the parallelogram ABCD results in image A’B’C’D’

Mathematics
2 answers:
vodka [1.7K]3 years ago
6 0
This would be a reflection.
jeka943 years ago
6 0
This would be a reflection in the horizontal line
y = 3!
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Help! I'm a little stumped when it comes to variables in matrices. An explanation would be super rad!
iris [78.8K]

Answer:

30

Step-by-step explanation:

To find the determinant of a 3x3 matrix, you can use this method. (See picture.)

Start with the first number in the top row, and block off the row and column.  A 2x2 matrix will be left.  Find the determinant of this 2x2 matrix, and multiply it by the number in the top row.

Repeat for the other two numbers in the top row.  Add the first result, subtract the second, and add the third.

det A = -2 [(3)(-5) − (a)(0)] − 2 [(0)(-5) − (a)(0)] + b [(0)(0) − (3)(0)]

det A = -2 (3)(-5) − 0 + 0

det A = 30

8 0
2 years ago
An interior automotive supplier places several electrical wires in a harness.Apull test measures the force required to pull spli
oksano4ka [1.4K]

Answer:

a) For this case we can use the following R code to construct the qq plot

> data<-c(28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4)

# The above line is in order to store the data in a vector

> qqnorm(data, pch = 1, frame = FALSE)

# The line above is in order to calculate the quantiles from the data assumin Normal distribution

> qqline(data, col = "steelblue", lwd = 2)

# The line above is in order to put a line for the theoretical dsitribution

The result is on the figure attached.

b) For this case as we can see on the figure attached the calculated quantiles are not far from the theorical quantiles given byt the straaigth blue line so then we can conclude that the distribution seems to be normal.

Step-by-step explanation:

For this case we have the following data:

28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4

The quantile-quantile or q-q plot is a graphical procedure in order to check the validity of a distributional assumption for a data set. We just need to calculate "the theoretically expected value for each data point based on the distribution in question".

If the values are asusted to the assumed distribution, we will see that "the points on the q-q plot will fall approximately on a straight line"

For this case our distribution assumed is normal.

Part a

For this case we can use the following R code to construct the qq plot

> data<-c(28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4)

# The above line is in order to store the data in a vector

> qqnorm(data, pch = 1, frame = FALSE)

# The line above is in order to calculate the quantiles from the data assuming Normal distribution (0,1)

> qqline(data, col = "steelblue", lwd = 2)

# The line above is in order to put a line for the theoretical distribution

The result is on the figure attached.

Part b

For this case as we can see on the figure attached the calculated quantiles are not far from the theorical quantiles given byt the straaigth blue line so then we can conclude that the distribution seems to be normal.

4 0
3 years ago
Can somebody step by step explain how to solve this problem??<br><br> (3x^2y)(-7xy^3)
charle [14.2K]

Answer:

\boxed{\bold{-21x^3y^4}}

Explanation:

[ Step One ] Remove Parenthesis: (a) = a

\bold{-3x^2y\cdot \:7xy^3}

[ Step Two ] Multiply: \bold{3\cdot \:7=21}

\bold{-21x^2xy^3y}

[ Step Three ] Apply Exponent Rule \bold{\:a^b\cdot \:a^c=a^{b+c}: \ x^2x=\:x^{2+1}=\:x^3}

\bold{-21x^3y^3y}

[ Step Four ] Apply Exponent Rule: \bold{y^3y=\:y^{1+3}=\:y^4}

\bold{-21x^3y^4}

[ \boxed{\bold{Final \ Answer}} ]

➤ \bold{-21x^3y^4}

\boxed{\bold{Mordancy}}

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3 years ago
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I need help with calculus
alexdok [17]

Answer:

Step-by-step explanation:

5 0
3 years ago
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