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bija089 [108]
3 years ago
15

Find the difference -11 - -5, 25 - (-3) ,-7 - (-2), 4 - 15, 6 - (-9)

Mathematics
1 answer:
Leviafan [203]3 years ago
7 0

Answer:

-11-(-5)= -6

25-(-3)= 28

-7-(-2)= -5

4-15= -11

6-(-9)= 15

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he triangles below are similar. Triangle Y X Z. Side Y X is 6 centimeters, X Z is 7 centimeters, and Z Y is 3 centimeters. Trian
MissTica
  • YX=6
  • XZ=7
  • ZY=3

And

  • AB=12
  • BC=6
  • AC=14

Check

  • AB/YX=BC/ZY=AC/XZ
  • 12/6=6/3=14/7
  • 2=2=2

Hence

  • ABC=XYZ

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Option C

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Pani-rosa [81]
Multiply 1st equation by 5
-5x + 10y = -20

now you have
-5x + 10y = -20
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answer
C. the system has infinitely many solutions
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What is the equation of the following line (0,0) and (-4,8)
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the equation using the point slope formula is

y=−2x

I hope this helps! :)

-Ayden

8 0
4 years ago
PLEASE HURRY! I'll mark the first person who answers as brainliest!
Nana76 [90]

Answer:

7 and 8

Step-by-step explanation:

Take the square root of 53 and the answer in decimal form is

7.28010988

is between 7 and 8

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3 years ago
Let X represent the amount of energy a city uses (in megawatt-hours) in the Kanto region. Let Y represent the amount of mismanag
Setler [38]

Answer:

Part 2: The probability of X≤2 or X≥4 is 0.5.

Part 3: The value of marginal probability of y is f_y(y)=\frac{10-y}{32} for  2\leq y\leq 10

Part 4:The value of E(y) is 4.6667.

Part 5:The value of f_{xy}(x) is \frac{2}{10-y} for 2\leq y\leq 2x\leq 10

Part 6:The value of M_{x,y}(y) is \frac{y+10}{4}

Part 7:The value of E(x) is 3.6667.

Part 8:The value of E(x,y) is 36.

Part 9:The value of Cov(x,y) is 18.8886.

Part 10:X and Y are not independent variables as f_{xy}(x,y)\neq f_x(x).f_y(y)\\

Step-by-step explanation:

As the complete question is here, however some of the values are not readable, thus the question is found online and is attached herewith.

From the given data, the joint distribution is given as

f(x,y)=\frac{1}{16} for 2\leq y\leq 2x\leq 10

Now the distribution of x is given as

f_x(x)=\int\limits^{\infty}_{-\infty} {f(x,y)} \, dy

Here the limits for y are 2\leq y\leq 2x So the equation becomes

f_x(x)=\int\limits^{\infty}_{-\infty} {f(x,y)} \, dy\\f_x(x)=\int\limits^{2x}_{2} \frac{1}{16} \, dy\\f_x(x)=\frac{1}{16} (2x-2)\\f_x(x)=\frac{x-1}{8}                        \,\,\,\,\,\,\,\,\,\,\,\, for \,\,\,\,\,\,\,\,\,\ 1\leq x\leq 5

Part 2:

The probability is given as

P(X\leq 2 U X\geq 4)=\int\limits^2_1 {f_x(x)} \, dx +\int\limits^5_4 {f_x(x)} \, dx\\P(X\leq 2 U X\geq 4)=\int\limits^2_1 {\frac{x-1}{8}} \, dx +\int\limits^5_4 {\frac{x-1}{8}} \, dx\\P(X\leq 2 U X\geq 4)=\frac{1}{16}+\frac{7}{16}\\P(X\leq 2 U X\geq 4)=0.5

So the probability of X≤2 or X≥4 is 0.5.

Part 3:

The distribution of y is given as

f_y(y)=\int\limits^{\infty}_{-\infty} {f(x,y)} \, dx

Here the limits for x are y/2\leq x\leq 5 So the equation becomes

f_y(y)=\int\limits^{\infty}_{-\infty} {f(x,y)} \, dx\\f_y(y)=\int\limits^{5}_{y/2} \frac{1}{16} \, dx\\f_y(y)=\frac{1}{16} (5-\frac{y}{2})\\f_y(y)=\frac{10-y}{32}                        \,\,\,\,\,\,\,\,\,\,\,\, for \,\,\,\,\,\,\,\,\,\ 2\leq y\leq 10

So the value of marginal probability of y is f_y(y)=\frac{10-y}{32} for  2\leq y\leq 10

Part 4

The value is given as

E(y)=\int\limits^{10}_2 {yf_y(y)} \, dy\\E(y)=\int\limits^{10}_2 {y\frac{10-y}{32}} \, dy\\E(y)=\frac{1}{32}\int\limits^{10}_2 {10y-y^2} \, dy\\E(y)=4.6667

So the value of E(y) is 4.6667.

Part 5

This is given as

f_{xy}(x)=\frac{f_{xy}(x,y)}{f_y(y)}\\f_{xy}(x)=\frac{\frac{1}{16}}{\frac{10-y}{32}}\\f_{xy}(x)=\frac{2}{10-y}

So the value of f_{xy}(x) is \frac{2}{10-y} for 2\leq y\leq 2x\leq 10

Part 6

The value is given as

\geq M_{x,y}(y)=E(f_{xy}(x))=\int\limits^5_{y/2} {x f_{xy}(x)} \, dx \\M_{x,y}(y)=\int\limits^5_{y/2} {x \frac{2}{10-y}} \, dx \\M_{x,y}(y)=\frac{2}{10-y}\left[\frac{x^2}{2}\right]^5_{\frac{y}{2}}\\M_{x,y}(y)=\frac{2}{10-y}\left(\frac{25}{2}-\frac{y^2}{8}\right)\\M_{x,y}(y)=\frac{y+10}{4}

So the value of M_{x,y}(y) is \frac{y+10}{4}

Part 7

The value is given as

E(x)=\int\limits^{5}_1 {xf_x(x)} \, dx\\E(x)=\int\limits^{5}_1 {x\frac{x-1}{8}} \, dx\\E(x)=\frac{1}{8}\left(\frac{124}{3}-12\right)\\E(x)=\frac{11}{3} =3.6667

So the value of E(x) is 3.6667.

Part 8

The value is given as

E(x,y)=\int\limits^{5}_1 \int\limits^{10}_2 {xyf_{x,y}(x,y)} \,dy\, dx\\E(x,y)=\int\limits^{5}_1 \int\limits^{10}_2 {xy\frac{1}{16}} \,dy\, dx\\E(x,y)=\int\limits^{5}_1 \frac{x}{16}\left[\frac{y^2}{2}\right]^{10}_2\, dx\\E(x,y)=\int\limits^{5}_1 3x\, dx\\\\E(x,y)=3\left[\frac{x^2}{2}\right]^5_1\\E(x,y)=36

So the value of E(x,y) is 36

Part 9

The value is given as

Cov(X,Y)=E(x,y)-E(x)E(y)\\Cov(X,Y)=36-(3.6667)(4.6667)\\Cov(X,Y)=18.8886\\

So the value of Cov(x,y) is 18.8886

Part 10

The variables X and Y are considered independent when

f_{xy}(x,y)=f_x(x).f_y(y)\\

Here

f_x(x).f_y(y)=\frac{x-1}{8}\frac{10-y}{32} \\

And

f_{xy}(x,y)=\frac{1}{16}

As these two values are not equal, this indicates that X and Y are not independent variables.

4 0
3 years ago
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