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2 years ago

X2-3x=2x+14 is my question

Mathematics

1 answer:

Paha777 [63]2 years ago

4 0

Answer:

X= 7, -2

Step-by-step explanation:

if ur asking for X but if yea that's the answer for X

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LOTS OF POINTS, WILL MARK BRAINLIEST! pls show working!!!!!

sp2606 [1]

Answer: ΔTAU ≈ ΔUAV ≈ ΔTUV

Step-by-step explanation:

I'm not really sure what "work" you really need; this is a problem that can be solved easily by simply looking at the triangles and seeing which sides have the same ratio of distances for each side.

Best of luck with your assignment. :) Feel free to give me Brainliest if you feel this helped. Have a good day.

8 0

1 year ago

<img src="https://tex.z-dn.net/?f=f%20-%20354%20%3D%201221" id="TexFormula1" title="f - 354 = 1221" alt="f - 354 = 1221" align="

alukav5142 [94]

$f-354=1221$ add 354 to both sides

$f+354-354=1221+354\\\\\boxed{f=1,575}\to\boxed{D.}$

6 0

3 years ago

Let X and Y be discrete random variables. Let E[X] and var[X] be the expected value and variance, respectively, of a random vari

Ulleksa [173]

Answer:

(a) $E[X+Y]=E[X]+E[Y]$

(b) $Var(X+Y)=Var(X)+Var(Y)$

Step-by-step explanation:

Let X and Y be discrete random variables and E(X) and Var(X) are the Expected Values and Variance of X respectively.

(a)We want to show that E[X + Y ] = E[X] + E[Y ].

When we have two random variables instead of one, we consider their joint distribution function.

For a function f(X,Y) of discrete variables X and Y, we can define

$E[f(X,Y)]=\sum_{x,y}f(x,y)\cdot P(X=x, Y=y).$

Since f(X,Y)=X+Y

$E[X+Y]=\sum_{x,y}(x+y)P(X=x,Y=y)\\=\sum_{x,y}xP(X=x,Y=y)+\sum_{x,y}yP(X=x,Y=y).$

Let us look at the first of these sums.

$\sum_{x,y}xP(X=x,Y=y)\\=\sum_{x}x\sum_{y}P(X=x,Y=y)\\\text{Taking Marginal distribution of x}\\=\sum_{x}xP(X=x)=E[X].$

Similarly,

$\sum_{x,y}yP(X=x,Y=y)\\=\sum_{y}y\sum_{x}P(X=x,Y=y)\\\text{Taking Marginal distribution of y}\\=\sum_{y}yP(Y=y)=E[Y].$

Combining these two gives the formula:

$\sum_{x,y}xP(X=x,Y=y)+\sum_{x,y}yP(X=x,Y=y) =E(X)+E(Y)$

Therefore:

$E[X+Y]=E[X]+E[Y] \text{ as required.}$

(b)We want to show that if X and Y are independent random variables, then:

$Var(X+Y)=Var(X)+Var(Y)$

By definition of Variance, we have that:

$Var(X+Y)=E(X+Y-E[X+Y]^2)$

$=E[(X-\mu_X +Y- \mu_Y)^2]\\=E[(X-\mu_X)^2 +(Y- \mu_Y)^2+2(X-\mu_X)(Y- \mu_Y)]\\$Since we have shown that expectation is linear$\\=E(X-\mu_X)^2 +E(Y- \mu_Y)^2+2E(X-\mu_X)(Y- \mu_Y)]\\=E[(X-E(X)]^2 +E[Y- E(Y)]^2+2Cov (X,Y)$