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suter [353]
3 years ago
8

(9+4a)+(4+3c)=? ​(Simplify your​ answer.)

Mathematics
2 answers:
expeople1 [14]3 years ago
4 0

Answer:

4a+3c+13

Step-by-step explanation:

mr Goodwill [35]3 years ago
3 0

Answer:

= 4a + 3c + 13

Step-by-step explanation:

(9+4a)+(4+3c)

= 9 + 4a + 4 + 3c

= 4a + 3c + 13

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The surface area of a rectangle prism is 166 square feet. The surface area of a similar rectangular prism is 1494 square feet. I
vovangra [49]
The ratio surface area of two similar rectangular prism has the relationship of square time of the ratio of length. So the 1494/166=9=3². So the length of two has ratio of 3. So the length of the larger one is 5*3=15 feet.
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What does interior angle A of the polygon in the figure equal?
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Help me y’all! Need to turn this in tonight
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Answer: y = -1

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8 0
2 years ago
In the United States, the average public school teacher currently earns an annual salary near $55,202. Reported national average
Makovka662 [10]

Answer:

i believe it is c

Step-by-step explanation:

6 0
3 years ago
Let X ~ N(0, 1) and Y = eX. Y is called a log-normal random variable.
Cloud [144]

If F_Y(y) is the cumulative distribution function for Y, then

F_Y(y)=P(Y\le y)=P(e^X\le y)=P(X\le\ln y)=F_X(\ln y)

Then the probability density function for Y is f_Y(y)={F_Y}'(y):

f_Y(y)=\dfrac{\mathrm d}{\mathrm dy}F_X(\ln y)=\dfrac1yf_X(\ln y)=\begin{cases}\frac1{y\sqrt{2\pi}}e^{-\frac12(\ln y)^2}&\text{for }y>0\\0&\text{otherwise}\end{cases}

The nth moment of Y is

E[Y^n]=\displaystyle\int_{-\infty}^\infty y^nf_Y(y)\,\mathrm dy=\frac1{\sqrt{2\pi}}\int_0^\infty y^{n-1}e^{-\frac12(\ln y)^2}\,\mathrm dy

Let u=\ln y, so that \mathrm du=\frac{\mathrm dy}y and y^n=e^{nu}:

E[Y^n]=\displaystyle\frac1{\sqrt{2\pi}}\int_{-\infty}^\infty e^{nu}e^{-\frac12u^2}\,\mathrm du=\frac1{\sqrt{2\pi}}\int_{-\infty}^\infty e^{nu-\frac12u^2}\,\mathrm du

Complete the square in the exponent:

nu-\dfrac12u^2=-\dfrac12(u^2-2nu+n^2-n^2)=\dfrac12n^2-\dfrac12(u-n)^2

E[Y^n]=\displaystyle\frac1{\sqrt{2\pi}}\int_{-\infty}^\infty e^{\frac12(n^2-(u-n)^2)}\,\mathrm du=\frac{e^{\frac12n^2}}{\sqrt{2\pi}}\int_{-\infty}^\infty e^{-\frac12(u-n)^2}\,\mathrm du

But \frac1{\sqrt{2\pi}}e^{-\frac12(u-n)^2} is exactly the PDF of a normal distribution with mean n and variance 1; in other words, the 0th moment of a random variable U\sim N(n,1):

E[U^0]=\displaystyle\frac1{\sqrt{2\pi}}\int_{-\infty}^\infty e^{-\frac12(u-n)^2}\,\mathrm du=1

so we end up with

E[Y^n]=e^{\frac12n^2}

3 0
3 years ago
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