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3 years ago

Which geologic feature does not occur at a convergent boundary?

Mathematics

1 answer:

irina [24]3 years ago

4 0

I think the valley becausr convergent is pushing together and you cany get a valley unless its divergent

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The moment of intertia about the z-axis of the solid shown on the right with density deltaδequals=1 is upper i subscript z base

Ratling [72]

<span>私の名前はあなたのビジネスのどれでもありません</span>

8 0

3 years ago

How much must be deposited today into the following account in order to have $35,000 in 7 years for a down payment on a house?

Rom4ik [11]

Answer:

The amount that must be deposited is $ 19973.87.

Step-by-step explanation:

We have a relation between future value present value as:

F= P $(1 +\frac{r}{n} )^{nt}$

F=future value

P=present value

r=rate (as a decimal)

n=number of compounding periods per year

t=number of years

Now,

assume rate as 8%

35000= P $(1+\frac{0.08}{12} )^{12*7}$

or, 35000= P × $1.0067^{84}$

or, P = $\frac{35000}{1.7522}$

or, P = $ 19973.87

So you must deposit $ 19973.87 today.

7 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.