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Nat2105 [25]
3 years ago
5

Drag steps in the given order to evaluate this expression. (−3)(2)−7(−3)−10

Mathematics
2 answers:
patriot [66]3 years ago
8 0
Step 1:
 
Multiply the numbers in parentheses:
 (-3 * 2) - (7 * (- 3)) - 10
 -6 - (- 21) -10
 Step 2:
 
Equal signs are added:
 -6 + 21-10
 Step 3:
 
Make the algebraic sum:
 -6 + 21-10 = 5
 Answer:
 
the final result is 5.
Ad libitum [116K]3 years ago
8 0

Answer:

(-3)(2) - 7 ( -3) -10\\= (-6) - (-21) -10\\= -16 + 21 - 10\\= -5\\

Step-by-step explanation:

We will follow the rule of BODMAS

B - Bracket Of

D - Division

M = Multiplication

A = Addition

S = Subtraction

On solving the give equation as per the order of BODMAS, we get -

(-3)(2) - 7 ( -3) -10\\= (-6) - (-21) -10\\= -16 + 21 - 10\\= -5\\

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How do you say 506,709 in expanded form?
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Five hundred six thousand seven hundred nine.
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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)

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3 years ago
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Answer:

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so 4 + 36x is your expression because you can't add numbers with different variables or if they don't even have one.

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