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Ksju [112]
3 years ago
7

42 is 64% of what number

Mathematics
2 answers:
steposvetlana [31]3 years ago
4 0
Answer: x = 65.63
Explanation:
We have, 64% × x = 42 or, 64/100 × x = 42
Multiplying both sides by 100 and dividing both sides by 64, we have x = 42 × 100 64
x = 65.63

Pani-rosa [81]3 years ago
4 0

Answer:

the answer is 65.625, 42 is 64% of 65.625

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What is an angle between a side of a polygon and the extension of its adjacent side
jek_recluse [69]
I would say that the angle would be an exterior angle because it's usually between the side of the polygon connected by a line as an extension of the adjacent side. 

here's an example. hope it helps!

8 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
Enlist education system found in Nepal​
Gelneren [198K]

Answer:

Education in Nepal was long based on home-schooling and gurukulas.[citation needed] The first formal school (Durbar School), established by Jung Bahadur Rana in 1853, was intended for the elite. The birth of Nepalese democracy in 1951 opened its classrooms to a more diverse population.[citation needed] Education in Nepal from the primary school to the university level has been modeled from the very inception on the Indian system, which is in turn the legacy of the old British Raj.[1]

Step-by-step explanation:

Mark as brainliest

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8 0
3 years ago
What is the value of the x variable in the solution to the following system of equations?
Mazyrski [523]
Correct answer is A.

3x + 2y = 8
\\2x + 3y = 2 
\\
\\9x+6y=24
\\-4x-6y=-4
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\\5x=20
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5 0
3 years ago
Read 2 more answers
If this is the graph of f(x) = a^(x+h) + k then
Natali [406]

Answer:

The domain is (-∞,∞) and range is (k,∞)

Step-by-step explanation:

The graph is given as a^(x+h)+k.

When x =0, we have f(x) a^h+k= y intercept

Consider the exponential function y = a^x.

This is defined for domain all real numbers and range = (0,infinity) for all positive a.

This function is transformed into our function by horizontal shift of h units to left and vertical units of k units up.

i.e. Y = y-k and X = x-h

Since x has domain as set of all real numbers X also set of real numbers

So domain is (-∞,∞)

Since range of original graph is (0,∞), we have Y minimum value as k and max as infinity.

Range = (k,∞)


5 0
3 years ago
Read 2 more answers
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