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3 years ago

Find a. Round to the nearest tenth:

Mathematics

1 answer:

Ulleksa [173]3 years ago

6 0

Step-by-step explanation:

In the following triangle, a= ? , b= 2cm.

m<B= 105° , m<C = 15° ,m< A =?

Now, we know that sum of the interior angles of the triangle = 180°

m<B+m<C +m< A =180°

105°+15°+m< A=180°

m< A= 180- 120° = 60°

$\frac{ \sin( A) }{a} = \frac{ \sin(B) }{b}$

$\frac{ \sin(60) }{a} = \frac{ \sin(105) }{2}$

$a = \frac{ \sin(60) }{ \sin(105) } \times 2$

$a = 1.79$

$a = 1.8$

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Answer:

slope = 0

Step-by-step explanation:

calculate the slope m using the slope formula

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2 years ago

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Find the value of kk for which the constant function x(t)=kx(t)=k is a solution of the differential equation 5t3dxdt+2x−2=05t3dx

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Given the differential equation

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The solution is as follows:

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3 years ago

The director of admissions at Kinzua University in Nova Scotia estimated the distribution of student admissions for the fall sem

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Answer:

In order to calculate the expected value we can use the following formula:

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

And if we use the values obtained we got:

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Step-by-step explanation:

Let X the random variable that represent the number of admisions at the universit, and we have this probability distribution given:

X 1060 1400 1620

P(X) 0.5 0.1 0.4

In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".

The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).

And the standard deviation of a random variable X is just the square root of the variance.

In order to calculate the expected value we can use the following formula:

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

And if we use the values obtained we got:

$E(X)=(1060*0.5) +(1400*0.1) +(1620*0.4)=1318$

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2 years ago

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satela [25.4K]

Answer:

The probability of SFS and SSF are same, i.e. P (SFS) = P (SSF) = 0.1311.

Step-by-step explanation:

The probability of a component passing the test is, P (S) = 0.79.

The probability that a component fails the test is, P (F) = 1 - 0.79 = 0.21.

Three components are sampled.

Compute the probability of the test result as SFS as follows:

P (SFS) = P (S) × P (F) × P (S)

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Compute the probability of the test result as SSF as follows:

P (SSF) = P (S) × P (S) × P (F)

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Thus, the probability of SFS and SSF are same, i.e. P (SFS) = P (SSF) = 0.1311.

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3 years ago

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emmasim [6.3K]

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