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VARVARA [1.3K]
3 years ago
7

Solve y – 7 > 3 + 2y A) y -10 D) y > -10

Mathematics
1 answer:
Anika [276]3 years ago
7 0

Answer:

D. -y > 10

Step-by-step explanation:

First, move the variable (+ 2y) to the left-hand side and change its sign.

y - 2y - 7 > 3

Then, move the constant (+ 7) to the right-hand side and change its sign.

y - 2y > 3 + 7

Then, collect the like terms (y - 2y)

-y > 3 + 7

Finally, add the numbers (3 + 7). That will get you your final answer.

-y > 10

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Answer both there’s a part A and B
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6

Step-by-step explanation:

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Christine purchased a prepaid phone card for $20. Long distance calls cost 18 cents a minute using this card. Christine used her
Luda [366]

Answer:

4 minutes and 32 seconds

Step-by-step explanation:

card $20.00-money left over $15.68            $20.00-$15.68  4.32

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3 years ago
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.

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3 years ago
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ziro4ka [17]

Answer:

72

Step-by-step explanation:

45% did not get shiped so 160*.45=72

6 0
3 years ago
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