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patriot [66]
3 years ago
10

Find the area of the right triangle ADC

Mathematics
2 answers:
Igoryamba3 years ago
4 0
A= 1/2(bh)
A= 1/2(8)(4)
A= 16
vesna_86 [32]3 years ago
3 0

Answer:

32/2= 16

Step-by-step explanation:

formula for area of triangle is base x height divided by 2

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Alika [10]

The slope of the line is 1

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3 years ago
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Write a new function that represents a transformation to the parent function if the new function shifts right 5 units and up 3 u
irga5000 [103]

Answer:

Let's define two transformations.

Vertical translation.

If we have a function f(x), a vertical translation of N untis is written as:

g(x) = f(x) + N

If N is positive, then the translation is upwards

If N is negative, then the translation is downwards.

Horizontal translation.

If we have a function f(x), a horizontal translation of N units is written as:

g(x) = f(x - N)

if N is positive, then the translation is to the right

If N is negative, then the translation is to the left.

Now we have a function g(x) that is a transformation of a parent function f(x) (we actually do not know which parent function, so i assume f(x) = x^2) such that we have a shift right 5 units and up 3 units.

Then:

g(x) = f(x - 5) + 3

and again, using f(x) = x^2

g(x) = (x - 5)^2  + 3

6 0
3 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.

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Anvisha [2.4K]

Answer:

Table 1

Step-by-step explanation:

Check Table 1:-

x = -4 gives y = (-4)^2 + 4(-4) = 0

x = -2 gives y = (-2)^2 - 2(-2) = -4

x = 0 gives 0 + 0 = 0

x = 1 gives 1^2 + 4 = 5

That's the one!

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Answer:

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Step-by-step explanation:

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