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Marysya12 [62]
3 years ago
11

Carl, gilda, conroy, and kyla are the four candidates in a school election. carl 2/5 received of the votes, gilda received 10% o

f the votes, and conroy 1/4 received of the votes. if kyla received all of the remaining votes, what percentage of the votes did she receive?
Mathematics
2 answers:
butalik [34]3 years ago
8 0
She received 25% of the votes.
2/5=40%
1/4=25%
10% + 40%+25%=75%
75%-100%=25%
Masteriza [31]3 years ago
3 0
2/5=40%
10%
1/4=25%
100-75=25%
She gets 25% of the votes
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MrRa [10]

Answer:

see the explanation

Step-by-step explanation:

Let

x ----> the number of hours Eli worked

y ----> the number of hours Samantha worked

we know that

Eli and they ironed 400 shirts between them

so

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Samantha worked 2 more hours than Eli

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solve the system by substitution

substitute equation B in equation A

solve for x

Find the value of y

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therefore

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Answer:

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Step-by-step explanation:

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Answer:

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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)

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solmaris [256]

Answer : 12cm^2

Step-by-step explanation:

A = bh/2

A = 8 * 3 /2

A = 24/2

A = 12 cm^2

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