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Viefleur [7K]
4 years ago
5

Simplify √5 • √8. A.)2√10 B.)4√10 C.)√40 D.)√13

Mathematics
1 answer:
tresset_1 [31]4 years ago
5 0

Answer:

Simplify the radical by breaking the radical  up into a product of known factors.

2 √ 10

Step-by-step explanation:

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Help with this please.​
Irina-Kira [14]

Step-by-step explanation:

90 degree - 22 degree = 68 degree

use sin rule

sin90/x = sin68/56

x =60.4 degree

3 0
3 years ago
Substitute the given values into the​ formula, and solve for the unknown variable. A=bh
Veseljchak [2.6K]

Answer:

h = 7

Step-by-step explanation:

We are given the equation A=bh , and need to work out the unknown variable .

So we substitute the values of A and b given :

70 = (10)(h)

70 = 10 × h

Divide both sides by 10 :

70 ÷ 10 = h

h = 7

Hope this helped and have a good day

3 0
1 year ago
What is the difference of 5.9-2.2
vampirchik [111]
3.7 difference is subtraction and 5-2 is 3, 9-2 is 7
8 0
4 years ago
The area of a triangle is 24 square inches. What is the height of the triangle if the base length is 8 inches?
Basile [38]
The formula for the area of a ∆ is 1/2bh. So since you already have the area, solve for x.
24=\frac{1}{2}(8)x
24=4x
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The missing side is 6 inches long.
3 0
4 years ago
Read 2 more answers
) Explain why the sample midrange might be preferred to the sample mean as an estimator of the population mean.
Citrus2011 [14]

Answer:

It is a good Estimator of the Population Mean because the distribution of the sample midrange is just same as the distribution of the random variable.

Step-by-step explanation: from the table,

Minimum value = 34

maximum values = 1084

The sample mid-range can be computed as:

(Min.value + max.value)/2

(34 + 1084)/2

Sample mid-range = 55

The sample midrange uses only a small portion of the data, but can be heavily affected by outliers.

It provides information about the skewness and heavy-tailedness of the distribution which is just same as the distribution of the random variable.

The nature of this distribution is not intuitive but the Central Limit in which it will approach a normal distribution for large sample size.

5 0
3 years ago
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