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Greeley [361]
3 years ago
14

Decide whether the following situation is looking for the percent, the part, or the whole:The 14 compact cars sold by a dealer o

n Monday was 56% of the cars sold that day.
Mathematics
1 answer:
borishaifa [10]3 years ago
6 0

Answer:

  whole

Step-by-step explanation:

No question is posed.

If we assume we're interested in the number of cars sold on Monday, we have ...

  part = percent × whole

  14 = 56% × whole

It would seem that we're looking for the whole.

__

14/.56 = 25 cars were sold on Monday.

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muminat

Answer:a scale facter is a scale of how much is one each side or corner and the shape

Step-by-step explanation:

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2 years ago
Which expression is equal to p + (q + r)?
Svetach [21]
The answer should be a) (p+q)*r
7 0
3 years ago
Aline with a slope of contains the point (3.4). The point ( - 2 ) is also on the
Maru [420]

Answer:

Not Sure Without Slope

Step-by-step explanation:

you could use the formula y-y1=m(x-x1)(point slope form) where m is the slope, y1 is the first y point and x1 is the first x point.

For example if a line has slope 3 and passes through the points (5, 6), then the formula you would solve is y-6=3(x-5) to find the equation of the line in slope-intercept form and you should know what to do with everything else.

4 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
The diameter of a sphere is 2,160 mm. The diameter of a second sphere is 7,520 mm. Approximately how many times larger is the vo
fgiga [73]

Answer:

Approximately 42 times larger

Step-by-step explanation:

The diameter of a sphere is 2,160 mm.

The diameter of a second sphere is 7,520 mm.

To see how many times larger is the diameter of second sphere is than the diameter of the second sphere, we divide to get:

k =  \frac{7520}{2160}

k = 3.481

To see how many times larger the volume is, we cube both sides

{k}^{3}  =  {3.481}^{3}

This implies that

{k}^{3}  = 42.181

Therefore the volume of the second sphere is approximately 42 times larger

3 0
3 years ago
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