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In-s [12.5K]
3 years ago
12

A cylinder has a height of 19 centimeters and a radius of 6 centimeters. What is its volume?

Mathematics
1 answer:
Lunna [17]3 years ago
3 0

Answer:

2147.76 cm³

Step-by-step explanation:

using the formula for volume

πr²h

3.14×6²×19

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One inch is what part of one yard?<br><br> F. 1/12<br> G. 1/100<br> H. 1/3<br> J. 1/36
viva [34]

I think the answer is either:

J.1/36 or G.1/100

Because 1 yard is 0.027778 inch. So it has to be a really small fraction.

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A house was sold for $300,000 and a profit of 5% was made. Determine its
lara [203]

Answer:

285,000

Step-by-step explanation:

First, you need to figure out how much was profit. Multiply 300k by .05, which should give you 15,000. Then, subtract 15,000 from 300k to get 285k. hope this helps

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A grocery store sells tangerines in 2/5 kg bags. A customer bought 4 kg of tangerines for a school party. How many bags did he b
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10kg bags I believe
8 0
2 years ago
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Suppose each of the following data sets is a simple random sample from some population. For each dataset, make a normal QQ plot.
adell [148]

Answer:

a) For this case the histogram is not too skewed and we can say that is approximately symmetrical so then we can conclude that this dataset is similar to a normal distribution

b) For this case the data is skewed to the left and we can't assume that we have the normality assumption.

c) This last case the histogram is not symmetrical and the data seems to be skewed.

Step-by-step explanation:

For this case we have the following data:

(a)data = c(7,13.2,8.1,8.2,6,9.5,9.4,8.7,9.8,10.9,8.4,7.4,8.4,10,9.7,8.6,12.4,10.7,11,9.4)

We can use the following R code to get the histogram

> x1<-c(7,13.2,8.1,8.2,6,9.5,9.4,8.7,9.8,10.9,8.4,7.4,8.4,10,9.7,8.6,12.4,10.7,11,9.4)

> hist(x1,main="Histogram a)")

The result is on the first figure attached.

For this case the histogram is not too skewed and we can say that is approximately symmetrical so then we can conclude that this dataset is similar to a normal distribution

(b)data = c(2.5,1.8,2.6,-1.9,1.6,2.6,1.4,0.9,1.2,2.3,-1.5,1.5,2.5,2.9,-0.1)

> x2<- c(2.5,1.8,2.6,-1.9,1.6,2.6,1.4,0.9,1.2,2.3,-1.5,1.5,2.5,2.9,-0.1)

> hist(x2,main="Histogram b)")

The result is on the first figure attached.

For this case the data is skewed to the left and we can't assume that we have the normality assumption.

(c)data = c(3.3,1.7,3.3,3.3,2.4,0.5,1.1,1.7,12,14.4,12.8,11.2,10.9,11.7,11.7,11.6)

> x3<-c(3.3,1.7,3.3,3.3,2.4,0.5,1.1,1.7,12,14.4,12.8,11.2,10.9,11.7,11.7,11.6)

> hist(x3,main="Histogram c)")

The result is on the first figure attached.

This last case the histogram is not symmetrical and the data seems to be skewed.

7 0
3 years ago
What is 0.167 times 180
Agata [3.3K]

Answer:

30.06

Step-by-step explanation:

6 0
2 years ago
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