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joja [24]
2 years ago
10

5 divided by 465 please give the answer

Mathematics
1 answer:
Andreas93 [3]2 years ago
8 0

Answer:

0.11111....

Step-by-step explanation:

. ......... .....

wait I was wrong

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Can a simplified answer can contain negative exponents?
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Answer:

it may possible but based on the answer.

Step-by-step explanation:

Negative value is a value which is less than 0

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Find the perimeter. Simplify your answer.
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Answer:

22w - 18  

Step-by-step explanation:

To find the perimeter we have to add up all the sides

10w-10+w+1+10w-10+w+1

combine light terms

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2 years ago
One math class has a greater number of students than the other. However,
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The classes could each have proportions of 5 boys to 6 girls, but they don’t necessarily have to be exactly 5 to 6. The number could 5 to 6 for one class, but it could also be 10 to 12 for another class, since 10 to 12 is a scale factor of 5 to 6.
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Simplify the expression: 6 + 3(x + 4) A 6 + 3x + 12 B 9x + 36 C 3x + 18 D 9x + 4
zepelin [54]

Answer:

C

Step-by-step explanation:

6 + 3(x + 4)

= 6 + 3x + 12

= 3x + 18

5 0
2 years ago
Consider a data set containing the following values: 70 65 71 78 89 68 50 75 The mean of the preceding values is 70.75. The devi
Leokris [45]

Answer:

If this is the sample data, the sample variance is 125.07 and the sample standard deviation is 11.18

If this is a population data, the population variance is 109.44 and the population standard deviation is 10.46

Step-by-step explanation:

We are given the following data-set:

70, 65, 71, 78, 89, 68, 50, 75

Deviations from the mean

–0.75, –5.75 , 0.25, 7.25, 18.25, –2.75, –20.75, 4.2

Sample size, n = 8

Sample:

\text{Standard Deviation} = \sqrt{\displaystyle\frac{\sum (x_i -\bar{x})^2}{n-1}}  

where x_i are data points, \bar{x} is the mean and n is the number of observations.

Sum of squares of differences =

0.5625 + 33.0625 + 0.0625 + 52.5625 + 333.0625 + 7.5625 + 430.5625 + 18.0625 = 875.5

s = \sqrt{\dfrac{875.5}{7}} = 11.18

\text{ Sample variance} = s^2 = 125.07

Population:

\text{Standard Deviation} = \sqrt{\displaystyle\frac{\sum (x_i -\bar{x})^2}{n}  

where x_i are data points, \bar{x} is the mean and n is the number of observations.

Sum of squares of differences =

0.5625 + 33.0625 + 0.0625 + 52.5625 + 333.0625 + 7.5625 + 430.5625 + 18.0625 = 875.5

\sigma = \sqrt{\dfrac{875.5}{8}} = 10.46

\text{ Population variance} = \sigma^2 = 109.44

7 0
3 years ago
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