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snow_lady [41]
3 years ago
10

What is a solid figure without any bases and with only one curved surface

Mathematics
2 answers:
zhenek [66]3 years ago
4 0
For example it would be ellipsoid  or sphere<span />
alisha [4.7K]3 years ago
3 0
The answer is cir le or sphere
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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
4 years ago
Jim Debt was reviewing the total accounts receivable. This month he received $80,000 from Credit customers. This represented 40
Lena [83]
<span>4x = 80,000 x= 80,000/.4 x = 200,000</span>
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3 years ago
In 2012 there were approximately 8,950 public libraries in the United States. A survey found that 76% of those libraries offered
choli [55]

Answer:

6,440

Step-by-step explanation:

i just did the math for this

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3 years ago
How can you use volume formulas to solve problems?
Katarina [22]
Well, it depends what shape you are using the volume formula for. If it's for a square (I'm assuming) then the volume formula would be:

Side^2

6 0
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Your bank account hos a bolance of -$17. You deposit $70. What is your new balance? Show work:​
Norma-Jean [14]

Answer:

53

Step-by-step explanation:

70-17= 53

3 0
3 years ago
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