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densk [106]
3 years ago
13

Twenty-seven minus 2 of a number (™) is not more than 36. What is the number?

Mathematics
1 answer:
-Dominant- [34]3 years ago
7 0
The correct answer would be c
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2 years ago
A clogged bathtub drains at a constant rate. The amount of water in the bathtub changes by -3.75 gallons in one hour. What is th
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-1.25  gallon is the change of the amount of water after 1/3 of an hour.

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3 years ago
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A 16-ft-long ramp rises at an angle of 18.5 degree. How long is the base of the ramp to the nearest foot?
Brilliant_brown [7]

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Step-by-step explanation: The bottom of the 14 foot ramp is equivalent to about 12.98 feet.

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3 years ago
A cook has 2 3/4 pounds of ground beef. How many quarter-pound burgers can he make?
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Answer:

  11

Step-by-step explanation:

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3 0
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
4 years ago
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