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Ilya [14]
3 years ago
7

The height of a triangle is 4 m more than twice the length of the base. The area of the triangle is 35 m^2 . Find the height of

the triangle
Mathematics
1 answer:
disa [49]3 years ago
6 0

Answer:

Step-by-step explanation:

Let the Base of the  △  be  x

Then the Height will be  2 x + 4

Area of △ = 1 2 b h

Where, b = b a s e , h = h e i g h t , A r e a = 35

(in this case)

Substitute the values into the equation → 35 = 1 2 ( 2 x + 4 ) ( x ) → 35 = ( 2 x + 4 ) 2 ( x ) →

35 = ( x + 2 ) ( x ) → 35 = x 2 + 2 x

Subtract  35  both sides

→ 0 = x ^2 + 2 x − 35

Rewrite the equation in the Standard form

x ^2 + 2 x − 35 = 0

Factor the equation

→ ( x + 7 ) ( x − 5 ) = 0

So we have  

x = − 7 , 5

numbers So  x = 5

They have asked us to find the Height

So, ⇒ H e i g h t = 2 x + 4 = 2

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You play in a soccer tournament, that consists of 5 games. Each game you win with probability .6, lose with probability .3, and
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Answer:

(a) The joint PMF of W, L and T is:

P(W,\ L,\ T)={5\choose (n_{W}!\times n_{L}!\times n_{T}!)}\times [0.60]^{n_{W}}\times [0.30]^{n_{L}}\times [0.10]^{n_{T}}

(b) The marginal PMF of W is:

P(W=w)={5\choose n_{W}!}\times 0.60^{n_{W}}\times (1-0.60)^{n-n_{W}}

Step-by-step explanation:

Let <em>X</em> = number of soccer games played.

The outcome of the random variable <em>X</em> are:

<em>W</em> = if a game won

<em>L</em> = if a game is lost

<em>T</em> = if there is a tie

The probability of winning a game is, P (<em>W</em>) = 0.60.

The probability of losing a game is, P (<em>L</em>) = 0.30.

The probability of a tie is, P (<em>T</em>) = 0.10.

The sum of the probabilities of the outcomes of <em>X</em> are:

P (W) + P (L) + P (T) = 0.60 + 0.30 + 0.10 = 1.00

Thus, the distribution of W, L and T is a appropriate probability distribution.

(a)

Now, the outcomes W, L and T are one experiment.

The distribution of <em>n</em> independent and repeated trials, each having a discrete number of outcomes, each outcome occurring with a distinct  constant probability is known as a Multinomial distribution.

The outcomes of <em>X</em> follows a Multinomial distribution.

The joint probability mass function of <em>W</em>, <em>L</em> and <em>T</em> is:

P(W,\ L,\ T)={n\choose (n_{W}!\times n_{L}!\times n_{T}!)}\times [P(W)]^{n_{W}}\times [P(L)]^{n_{L}}\times [P(T)]^{n_{T}}

The  soccer tournament consists of <em>n</em> = 5 games.

Then the joint PMF of W, L and T is:

P(W,\ L,\ T)={5\choose (n_{W}!\times n_{L}!\times n_{T}!)}\times [0.60]^{n_{W}}\times [0.30]^{n_{L}}\times [0.10]^{n_{T}}

(b)

The random variable <em>W</em> is defined as the number games won in the soccer tournament.

The probability of winning a game is, P (W) = <em>p</em> = 0.60.

Total number of games in the tournament is, <em>n</em> = 5.

A game is won independently of the others.

The random variable <em>W</em> follows a Binomial distribution.

The probability mass function of <em>W</em> is:

P(W=w)={5\choose n_{W}!}\times 0.60^{n_{W}}\times (1-0.60)^{n-n_{W}}

Thus, the marginal PMF of W is:

P(W=w)={5\choose n_{W}!}\times 0.60^{n_{W}}\times (1-0.60)^{n-n_{W}}

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