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UkoKoshka [18]
3 years ago
5

Find the value of both variables.

Mathematics
1 answer:
ella [17]3 years ago
8 0

\cos(45)  =  \frac{5 \sqrt{2} }{x}  \\  \frac{1}{ \sqrt{2} }  =  \frac{5 \sqrt{2} }{x}  \\ x = 10 \\  \\  \tan(45)  =  \frac{y}{5 \sqrt{2} }  \\ 1 =  \frac{y}{5 \sqrt{2} } \\ y = 5 \sqrt{2}

I hope I helped you ^_^

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Simplify the expression using the Distributive Property.<br><br> ½(10x + 20y)
marusya05 [52]

Answer:

Step-by-step explanation:

The distributive property affects both terms.

1/2 * 10x + 1/2 * 20 y

5x + 10 y <===== Answer

3 0
3 years ago
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In the game of​ roulette, a wheel consists of 38 slots numbered​ 0, 00,​ 1, 2,..., 36. To play the​ game, a metal ball is spun a
Oxana [17]

Answer:

E(X)=-0.0526

Sd(X)=5.763

Step-by-step explanation:

In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".

The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).

And the standard deviation of a random variable X is just the square root of the variance.  

Let X be a random variable which denotes the money you may win or lose on each spin.

In the game of roulette, a wheel consists of 38 slots. To play the game, a metal ball is spun around the wheel and is allowed to fall into one of the numbered slots. If the number of the slot the ball falls into matches the number you selected, we win $35; otherwise we lose $1.  So we have just one possibility to win and 37 of lose on an individual game.

___________________________

X            P(X)

___________________________

35           1/38

-1            37/38

___________________________

In order to calculate the expected value we can use the following formula:

E(X)=\sum_{i=1}^n X_i P(X_i)

And if we use the values obtained we got:

E(X)=(35)*(\frac{1}{38})+(-1)(\frac{37}{38})=-0.0526

In order to find the standard deviation we need to find first the second moment, given by :

E(X^2)=\sum_{i=1}^n X^2_i P(X_i)

And using the formula we got:

E(X^2)=(35^2)*(\frac{1}{38})+((-1)^2)(\frac{37}{38})=33.211

Then we can find the variance with the following formula:

Var(X)=E(X^2)-[E(X)]^2 =33.211-(-0.0526)^2 =33.208

And then the standard deviation would be given by:

Sd(X)=\sqrt{Var(X)}=\sqrt{33.208}=5.763

4 0
3 years ago
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Lemur [1.5K]
Try this solution, note, the suggested option is not the shortest way.

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3 years ago
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