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Arlecino [84]
2 years ago
5

Math, help, please! Find the value of x

Mathematics
2 answers:
pshichka [43]2 years ago
6 0

Answer:

x = 130

Step-by-step explanation:

A triangle always adds up to 180 de grees. If we do this we can find the value of x!!

33 + 97 + y = 180

130 + y = 180

180 - 130 = 50

Since the line x is on is a flat line and a flat line also equals 180, we will subtract the 50 from 180 to get x's value

180 - 50 = 130

Your answer is 130 :)

Have an amazing day!!

Please rate and mark brainliest!!

Aleksandr-060686 [28]2 years ago
3 0

Answer:

x = 50°

Step-by-step explanation:

if you know the measure of two angles in a triangle then the third angle measure will be 180 minus the sum of the other two

in this case the two interior angles add to 130

180-130 = 50

check:   33 + 97 + 50 should equal 180, and it does

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Determine whether a probability distribution is given. If a probability distribution is given, find its mean and standard deviat
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Answer:

E(X) = \sum_{i=1}^n X_i P(X_i) = 0*0.031 +1*0.156+ 2*0.313+3*0.313+ 4*0.156+ 5*0.031 = 2.5

We can find the second moment given by:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 0^2*0.031 +1^2*0.156+ 2^2*0.313+3^2*0.313+ 4^2*0.156+ 5^2*0.031 =7.496

And we can calculate the variance with this formula:

Var(X) =E(X^2) -[E(X)]^2 = 7.496 -(2.5)^2 = 1.246

And the deviation is:

Sd(X) = \sqrt{1.246}= 1.116

Step-by-step explanation:

For this case we have the following probability distribution given:

X          0            1        2         3        4         5

P(X)   0.031   0.156  0.313  0.313  0.156  0.031

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).  

We can verify that:

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

And P(X_i) \geq 0, \forall x_i

So then we have a probability distribution

We can calculate the expected value with the following formula:

E(X) = \sum_{i=1}^n X_i P(X_i) = 0*0.031 +1*0.156+ 2*0.313+3*0.313+ 4*0.156+ 5*0.031 = 2.5

We can find the second moment given by:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 0^2*0.031 +1^2*0.156+ 2^2*0.313+3^2*0.313+ 4^2*0.156+ 5^2*0.031 =7.496

And we can calculate the variance with this formula:

Var(X) =E(X^2) -[E(X)]^2 = 7.496 -(2.5)^2 = 1.246

And the deviation is:

Sd(X) = \sqrt{1.246}= 1.116

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