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wariber [46]
2 years ago
5

Austin is fertilizing his garden. The garden is in the shape of a rectangle. Its length is 14 feet and its width is 11 feet. Sup

pose each bag of fertilizer covers 22 square feet. How many bags will he need to cover the garden?
Mathematics
1 answer:
KATRIN_1 [288]2 years ago
4 0
First you need to find the area, the formula is A=LxW, multiply 14 by 11, that’s the area. If one back covers 22 ft we need to find how many 22s are in 154, to do that you divide. Make sense?

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If $16,400 is deposited into a CD paying 5.1% annually, how much will be in the account after 20 years? Enter your answer rounde
lesya692 [45]

16,400 x (1 + 0.051)^20 =

16400 x (1.051)^20 =

16400 x 2.70429659 =

$44,350.46 



4 0
3 years ago
Find the distance between (-8, 4) and (-8, -2).<br>10 units<br>2 units<br>6 units<br>8 units​
svp [43]

Answer:

10

Step-by-step explanation:

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.

4 0
3 years ago
What would the measure of DEC be
IceJOKER [234]
So if <AED =100 degrees result <BEC = 100 degrees too and 360-200=160
so 160/2 = 80 what mean that angle DEC=80 degrees 

hope helped 
3 0
3 years ago
If 1/6x + 3 = 7 what is x
kotykmax [81]

Answer:

x = 24

Step-by-step explanation:

1/6 x + 3 = 7

1/6 x = 4

x = 24

6 0
3 years ago
Read 2 more answers
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