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zalisa [80]
3 years ago
10

Their are 7 puppies must feed each puppy 1/2 cup each day how much feed do the go through each day

Mathematics
1 answer:
miv72 [106K]3 years ago
8 0

Answer:

14? i think thats what the answer is

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Two rectangles are similar. The ratio of the length of rectangle A to the length of rectangle B is 1:4. If the length of rectang
snow_lady [41]

Answer:

Hey have you tried on your own to make sure you understand it?

Step-by-step explanation:

6 0
2 years ago
Triangle DEF is a right triangle. What is the measure of ZEFD?<br> D<br> 57°<br> F<br> E
creativ13 [48]

Answer:

<h3>                33°</h3>

Step-by-step explanation:

Sum of measures of angles in any triangle is 180°

The maesure of right angle is 90°

So:  m∠EFD = 180° - 90° - 57° = 33°

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)

Since X and Y are independent, Cov(X,Y)=0

=Var(X)+Var(Y)

Therefore as required:

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

7 0
3 years ago
I need help ASAP (get brainliest)
maria [59]

Its B trust me i know

3 0
3 years ago
What value of m makes the equation 8am/4a5=2a6 true?
skelet666 [1.2K]

Answer:

m = 11

Step-by-step explanation:

11 - 5 = 6

4 0
3 years ago
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