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kap26 [50]
3 years ago
6

Runner is compared with the world record

Mathematics
2 answers:
34kurt3 years ago
7 0

Answer:

please add a different picture this one is fuzzy

Step-by-step explanation:

alex41 [277]3 years ago
4 0

Answer:

-0.42

Step-by-step explanation:

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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
1 1/2 as a fraction
Alik [6]

Answer:

1.5

Step-by-step explanation:

divide 1/2 and add 1

4 0
3 years ago
Which is the most appropriate operation to use to solve this problem? - Tony's job is to stack the cans on the shelves at the lo
seropon [69]
I would say division, you are trying to see how many cans can fit on those 15 shelves so you should do 585/15.
3 0
3 years ago
Read 2 more answers
at the bake sale the students earned $48.76. If there were 3 students, how much did each student earn?
Papessa [141]
Assuming each student was given equal compensation, take 48.76/3 = $16.25
5 0
4 years ago
Read 2 more answers
END OF THE YEAR QUIZ PLEASE ANSWER <br> ( question Is shown in photo)
lana66690 [7]

Answer:

B

Step-by-step explanation:

if you move the decimal over one you get 15 20 25. If you divide all of them by 5 you get 3 4 5. which is a right triangle.

3 0
3 years ago
Read 2 more answers
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