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jonny [76]
2 years ago
9

HELP 10 POINTS AND BRAINLIEST The triangles below are similar. In each traingle there is a 53°angle and a right angle. What is t

he measure of the third angle in each triangle?
37º
47º
53º
127º

Mathematics
2 answers:
Mrrafil [7]2 years ago
8 0

Answer:

Step-by-step explanation:

Since both triangles are similar, we know this because they have 2 angles in common, they both have the same third angle.

To find the third angle, we use the angle sum. The sum of angles in a triangle will always equal 180 degrees. We are given a right angle which is 90 degrees and another angle, which is 53 degrees. Knowing this:

90 + 53 + x = 180 (I have chosen to call the third angle x)

when rearranging this we get

180 - 90 - 53 = x

now we solve

x = 37 degrees

Hope this helps,

Cate

Andrei [34K]2 years ago
8 0

Answer:

37°

Step-by-step explanation:

Their size is irrelevant.

Since we know that the two other angles are 53° and 90°, we know that the last angle is 37° (180-53-90).

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answer is C
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2 years ago
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aalyn [17]
The answer would be 1,220,000mm.

You can do this if you convert all the measures into one unit. Let us convert all into km. 

The first one is already in km, so we do not need to covert it. 

Let's start with converting 1,220,000mm to km. 


There are 1, 000,000 mm in one km. 

1,220,000X \frac{1km}{1,000,000mm} = 1.22km

So there are 1.22km 
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Next, we have 120m. There are 1,000m in 1km.

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Answer:

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In order to find the variance we need to find first the second moment given by:

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And replacing we got:

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And the standard deviation is just the square root of the variance and we got:

Sd(X) = \sqrt{0.3075}= 0.5545

Step-by-step explanation:

Previous concepts

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).  

Solution to the problem

LEt X the random variable who represent the number of defective transistors. For this case we have the following probability distribution for X

X         0           1           2         3

P(X)    0.92     0.03    0.03     0.02

We can calculate the expected value with the following formula:

E(X) = \sum_{i=1}^n X_i P(X_i)

And replacing we got:

E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500

In order to find the variance we need to find first the second moment given by:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i)

And replacing we got:

E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300

The variance is calculated with this formula:

Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075

And the standard deviation is just the square root of the variance and we got:

Sd(X) = \sqrt{0.3075}= 0.5545

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statuscvo [17]

Answer:

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Step-by-step explanation:

P -R = 0

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