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Oliga [24]
3 years ago
9

m∠RSU=(5x+7)° and m∠UST=(9x−1)°. If ∠RSU and ∠UST are complementary, what is the measure of each angle?

Mathematics
1 answer:
ArbitrLikvidat [17]3 years ago
8 0

Answer:

37° and 53° respectively.

Step-by-step explanation:

We need to know that the angles are complementtary if ∠RSU + ∠UST = 90°. Then,

5x+7 + 9x-1 = 90

5x + 9x +7 -1 = 90

14x +6 = 90

14x = 90 - 6

14x = 84

x = 84/14

x = 6.

Then, the angle ∠RSU has measure 5(6)+ 7 = 30+7 = 37, and the angle ∠UST has measure 9(6) - 1 = 54-1 = 53.

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Answer:r=3q+2/3

Step-by-step explanation:

Step 1: Flip the equation.

3r-6=9q-4

Step 2: Add 6 to both sides.

3r-6+6=9q-4+6

3r=9q+2

Step 3: Divide both sides by 3.

3r/3=9q+2/3

r=3q+2/3

Hopefully it’s right

6 0
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A person places $290 in an investment account earning an annual rate of 2.2%, compounded continuously. Using the formula V = Pe^
Tomtit [17]

Answer:

<h2> $430.90</h2>

Step-by-step explanation:

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by applying the expression

V = Pe^{rt}

We have

V = 290e^{0.022*18}\\\\V=290e^{0.396}\\\\V=290*1.48586931755\\\\V=$430.90

Hence after 18years the money in the account will be $430.90

8 0
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Omar's gas tank is 1/10 full. After he buys 6 gallons of gas, it is 2/5 full. How many gallons can Omar's tank hold?
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It takes Mara 15 minutes to walk to her friends house 1 2/3 miles away. What is her walking pace in miles per hour?
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The lifetime X (in hundreds of hours) of a certain type of vacuum tube has a Weibull distribution with parameters α = 2 and β =
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f_X(x)=\begin{cases}\dfrac29xe^{-x^2/9}&\text{for }x\ge0\\\\0&\text{otherwise}\end{cases}

a. The expectation is

E[X]=\displaystyle\int_{-\infty}^\infty xf_X(x)\,\mathrm dx=\frac29\int_0^\infty x^2e^{-x^2/9}\,\mathrm dx

To compute this integral, recall the definition of the Gamma function,

\Gamma(x)=\displaystyle\int_0^\infty t^{x-1}e^{-t}\,\mathrm dt

For this particular integral, first integrate by parts, taking

u=x\implies\mathrm du=\mathrm dx

\mathrm dv=xe^{-x^2/9}\,\mathrm dx\implies v=-\dfrac92e^{-x^2/9}

E[X]=\displaystyle-xe^{-x^2/9}\bigg|_0^\infty+\int_0^\infty e^{-x^2/9}\,\mathrm x

E[X]=\displaystyle\int_0^\infty e^{-x^2/9}\,\mathrm dx

Substitute x=3y^{1/2}, so that \mathrm dx=\dfrac32y^{-1/2}\,\mathrm dy:

E[X]=\displaystyle\frac32\int_0^\infty y^{-1/2}e^{-y}\,\mathrm dy

\boxed{E[X]=\dfrac32\Gamma\left(\dfrac12\right)=\dfrac{3\sqrt\pi}2\approx2.659}

The variance is

\mathrm{Var}[X]=E[(X-E[X])^2]=E[X^2-2XE[X]+E[X]^2]=E[X^2]-E[X]^2

The second moment is

E[X^2]=\displaystyle\int_{-\infty}^\infty x^2f_X(x)\,\mathrm dx=\frac29\int_0^\infty x^3e^{-x^2/9}\,\mathrm dx

Integrate by parts, taking

u=x^2\implies\mathrm du=2x\,\mathrm dx

\mathrm dv=xe^{-x^2/9}\,\mathrm dx\implies v=-\dfrac92e^{-x^2/9}

E[X^2]=\displaystyle-x^2e^{-x^2/9}\bigg|_0^\infty+2\int_0^\infty xe^{-x^2/9}\,\mathrm dx

E[X^2]=\displaystyle2\int_0^\infty xe^{-x^2/9}\,\mathrm dx

Substitute x=3y^{1/2} again to get

E[X^2]=\displaystyle9\int_0^\infty e^{-y}\,\mathrm dy=9

Then the variance is

\mathrm{Var}[X]=9-E[X]^2

\boxed{\mathrm{Var}[X]=9-\dfrac94\pi\approx1.931}

b. The probability that X\le3 is

P(X\le 3)=\displaystyle\int_{-\infty}^3f_X(x)\,\mathrm dx=\frac29\int_0^3xe^{-x^2/9}\,\mathrm dx

which can be handled with the same substitution used in part (a). We get

\boxed{P(X\le 3)=\dfrac{e-1}e\approx0.632}

c. Same procedure as in (b). We have

P(1\le X\le3)=P(X\le3)-P(X\le1)

and

P(X\le1)=\displaystyle\int_{-\infty}^1f_X(x)\,\mathrm dx=\frac29\int_0^1xe^{-x^2/9}\,\mathrm dx=\frac{e^{1/9}-1}{e^{1/9}}

Then

\boxed{P(1\le X\le3)=\dfrac{e^{8/9}-1}e\approx0.527}

7 0
3 years ago
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