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DIA [1.3K]
3 years ago
7

Apply the distributive property to factor out the greatest common factor, 60 - 40y =

Mathematics
1 answer:
ASHA 777 [7]3 years ago
7 0

Answer:

GCF = 20

Step-by-step explanation:

he answer would be 20 so then you would get (3-2y) as a final answer

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The answer is b for both questions
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Two sides of a right triangle Measure 11 in and 15 in.
HACTEHA [7]

The sides could be 10.2 inches or 15.7 inches.

See the attached picture for the equations:

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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
Matt decides the length of his table will be 15 in. He calculates that the area of the table is 30 in. squared. Determine if Mat
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Answer:No Matt's calculation is not correct.

Step-by-step explanation:

We have to multiply by the number of the area.If it is 4 inches we multiply by 4

15 x 4 =60

A=4 inches squared

A=LxW (length x width )

so you can say that:

Matt is incorrect because He skipped  the step of multiplying 2 by 2 in the formula which is where we get 4 from.

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2 years ago
The area model shows 3 1/4 what is 3 Times 3 1/4
Aneli [31]

Answer:

Concept: Basic Multiplication

  1. You have 3 1/4 which can be said in decimal form to be 3.25
  2. You multiply it by 3 to get 9.75 or 9 3/4
  3. Hence D
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8 0
2 years ago
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