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Mathematics 13 Online
OpenStudy (anonymous):

what are the 1st partial derivatives of f(x) = 5yx+4y^2

OpenStudy (anonymous):

\[f_x = 5y + 0\\f_y = 5x + 8y\] When differentiating with respect to x, treat y as a constant and apply all normal diff. rules. Same when WRT y, but treat x as a constant.

OpenStudy (anonymous):

\[f_x = \frac{\delta}{\delta x} \\ f_y = \frac{\delta}{\delta y}\]

OpenStudy (anonymous):

I don't get it what is the d/dx is that like division?

OpenStudy (anonymous):

Those are curly ds signifying partial differentiation.

OpenStudy (anonymous):

similar to \[\frac{d}{dx}f(x) = f'(x)\] It's just notation. Liebniz vs Newtonian

OpenStudy (anonymous):

\[\frac{\delta}{\delta x}f(x) = f_x\] when partial wrt to x

OpenStudy (anonymous):

but what is 2 + 9? and how can i divide the numerator by a piece of the matrices in 4-space?

OpenStudy (anonymous):

....

OpenStudy (anonymous):

2 + 9 is 11. Let's say your numerator is 20. You have a denominator of 5. \[\frac{20}{5} = 4\] And the rest of your question makes no sense.

OpenStudy (anonymous):

Okay wow that is real amazing

OpenStudy (anonymous):

well if the partial fx is 5y then what is 2nd order partial wrt x?

OpenStudy (anonymous):

zero

OpenStudy (anonymous):

because there is no x in your expression, it is a constant

OpenStudy (anonymous):

ok

OpenStudy (anonymous):

what about 2nd order fxy

OpenStudy (anonymous):

\[f_{xy} = 5\]

OpenStudy (anonymous):

which by some theorem means \[f_{yx} = 5\]

OpenStudy (anonymous):

mixed order 2nd order partials are equivalent

OpenStudy (anonymous):

ok cool

OpenStudy (anonymous):

ty

OpenStudy (anonymous):

wait but what about fey

OpenStudy (anonymous):

Do you mean \[f_{yy}\]

OpenStudy (anonymous):

yes

OpenStudy (anonymous):

8

OpenStudy (anonymous):

OK but then what do i do if I can't figure out how to differentiate

OpenStudy (anonymous):

what do you mean?

OpenStudy (anonymous):

like if i have to use chain rule, i don'e like it

OpenStudy (anonymous):

lol

OpenStudy (anonymous):

how do i find expected value of continuous random variables

OpenStudy (anonymous):

? what class

OpenStudy (anonymous):

i don't know it just homework

OpenStudy (anonymous):

what class?

OpenStudy (anonymous):

probably theories?

OpenStudy (anonymous):

you mean probability?

OpenStudy (anonymous):

maybe, yes, yeah thats it

OpenStudy (anonymous):

So you have a PDF, like, f(x) = some expressions for various values of x (typically ranges since the variable X is continuous)

OpenStudy (anonymous):

so you find the limits of those ranges, and integrate each expression with respect to those limits, and sum your results after u anti-derive

OpenStudy (anonymous):

(after u calculate the integrals)

OpenStudy (anonymous):

that will be expected value (i.e., mean)

OpenStudy (anonymous):

i forgot, you need to multiply each expression by x before integrating that is \[E(X) = \int_{-\infty}^{\infty} xf(x)dx \]

OpenStudy (anonymous):

so like if f(x) = x^2 from 0 to 10 and 0, else, i integrate x*x^2 dx? so x^3 dx????

OpenStudy (anonymous):

yeah you can ignore the 0 cuz it will integrate to zero, so just integrate from 0 to 10 \[\int_{0}^{10}x^3dx\] and that will be expected value

OpenStudy (anonymous):

@Compassionate @shibainu @TheOcean @adrynicoleb

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