Simplify the square root of

Compared to an exponential function y = b where b > 0, a quadratic function grows: slower faster at the same rate sometimes f

Verizon [17]

Answer:

it's slower babe

6 0

3 years ago

On a coordinate plane, a point is at (negative 4, negative 4) and (negative 4, negative 10).

Valentin [98]

Answer:

Option C.

Step-by-step explanation:

Hey there!

The points are; (-4,-4) and (-4,-10).

Use distance formula.

$d = \sqrt{ {(x2 - x1)}^{2} + {(y2 - y1)}^{2} }$

~ Put all values.

$d = \sqrt{ {( - 4 + 4)}^{2} + ( { - 10 + 4)}^{2} }$

~ Simplify it.

$d = \sqrt{ {0}^{2} + ( { - 6)}^{2} }$

$d = \sqrt{36}$

Therefore, distance between the points is 6 units.

Hope it helps...

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 $n$ th 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

Which diagram represents the net of a cube? Circle all that apply.

Zigmanuir [339]

Answer:

B 100%

Step-by-step explanation:

3 0

1 year ago

17. New Schools expects an EBIT of $100,000 every year forever. The firm currently has no debt, and its cost of equity is 10 per

Natali5045456 [20]

Answer:

$880,000

Step-by-step explanation:

First note that the full meaning of EBIT is earning before interest and tax.

When the company does not have debt, it called unlevered (VU), while a company that has debt is called levered (VL) company. The VU and the VL of the company can be calculated using the VU and VL formula as follows:

Step 1. Calculation of VU

VU = [EBIT × (1 - tax rate)] ÷ cost of equity

= [$100,000 × (1 - 0.20)] ÷ 0.10

= [$100,000 × 0.80] ÷ 0.10

= $80,000 ÷ 0.10

= $800,000

Step 2. Calculation of VL

VL = VBC + (tax rate × conversion rate × VU)

= $800,000 + (0.20 × 0.5 × $800,000)

= $800,00 + $80,000

= $880,000

Therefore, the value of the firm will be $880,000 if it is converted to 50 percent debt.

3 0

3 years ago

Simplify the square root of –75