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Luda [366]
3 years ago
7

Find the missing side. Round your answer to the nearest tenth.

Mathematics
1 answer:
monitta3 years ago
4 0

Answer:12.4

Step-by-step explanation:

hyp=16,opp=x

sin 51°=\frac{x}{16}

cross multipy

sin 51° x 16 = x

x=0.7771 x 16

x≅12.4

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What is 4/16 ÷ 3/4 ​
Kobotan [32]

Answer:

4/12 simplified to 1/3.

Step-by-step explanation:

4/16 x 4/3 = 4/12

4/12 = 1/3

5 0
2 years ago
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attashe74 [19]
Rewrite it from least to greatest and set it up like shown

8 0
2 years ago
Determine whether a probability distribution is given. If a probability distribution is given, find its mean and standard deviat
drek231 [11]

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

6 0
3 years ago
PLEASE HELPPP!!!<br><br><br> THIS SHOULD BE EASY!
cupoosta [38]

Answer:

yes she can

Step-by-step explanation:

6 0
2 years ago
(a) The diagram below, not drawn to scale, shows a circle, centre 0. EH and EF are tangents to the circle. FOG and JOH are strai
posledela

Answer:

it is 6574 for the math problem

6 0
2 years ago
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