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lisov135 [29]
3 years ago
5

the utility bill for the Millers home was it in April with $132 42% of the bill was for gas and the rest for electricity how muc

h does the Millers pay for gas and how much did they pay for electricity
Mathematics
2 answers:
Anit [1.1K]3 years ago
6 0
In the given question, there are several data of immense importance. based on these data's the answer to the question can be easily deduced. it is already given that the total utility bill for the month of April in Millers house is $132 and 42% of the bill was paid for gas. remaining amount is paid as electricity charges.
Now
Amount of money paid for gas = 132 * (42/100) dollars
                                                  = 5544/100 dollars
                                                   = 55.44 dollars
Then
The amount of money paid for electricity = (132 - 55.44) dollars
                                                                   = 76.56 dollars
So the Millers paid 55.44 dollars for gas and 76.56 dollars for electricity in the month of April.
postnew [5]3 years ago
6 0

Answer:

Step-by-step explanation:

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5x -x + 3x =30,  first you combine like terms 5x + 3x-x=30

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c. y = -35*x + 105

Step-by-step explanation:

Lo que demos hacer es calcular los puntos cuando x = 0 y cuando x = 3, es decir el inicio y el fin del recorrido.

Cuando x es igual 0, y = 105, por lo tanto, la función sería:

y = A*x + 105

Cuando x = 3, y = 0, por lo tanto:

0 =  3*A +  105

resolvemos para A:

3*A =  -105

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A =  -35

Por lo tanto la función es:

y = -35*x + 105

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7 0
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Let X ~ N(0, 1) and Y = eX. Y is called a log-normal random variable.
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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

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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):

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so we end up with

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

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