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2 years ago

Is (1, 2) a solution to the inequality 6x - y> 3?

Mathematics

1 answer:

Lostsunrise [7]2 years ago

5 0

Answer:

Yes.

Step-by-step explanation:

To find the answer we will put it into the equation, since x = 1 and y = 2 we will write it like this, 6(1) - 2 > 3. Since 6 x 1 = 6, we will now subtract 6 from 2 which equals 4. Therefore, the equation is correct because 4 is bigger than 3.

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Answer:

10.87%

Step-by-step explanation:

Change in pay:

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Percent of change:

1.25/11.50*100% = 10.87% (rounded)

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3 years ago

You play two games against the same opponent. The probability you win the first game is 0.4. If you win the first game, the prob

koban [17]

Answer:

a) No, because the probabilities of winning the 2nd game are dependant on the result of the 1st game. The probabilities are different if you win or lose the first game.

b) P=0.42

c) P=0.08

X | P(X)

------------------

0 | 0.42

1 | 0.50

2 | 0.08

e) E(x)=0.66

s.d.=0.62

Step-by-step explanation:

a) No, because the probabilities of winning the 2nd game are dependant on the result of the 1st game. The probabilities are different if you win or lose the first game.

b) The probability of losing the first game is

$P(G_1=L)=1-P(G_1=W)=1-0.4=0.6$

The probability of losing the second game, given that the first game was lost is:

$P(G_2=L|G_1=L)=1-P(G_2=W|G_1=L)=1-0.3=0.7$

So the probability of losing both games is:

$P(G_2=L\&G_1=L)=P(G_1=L)*P(G_2=L|G_1=L)=0.6*0.7=0.42$

c) The probability of winning both games is:

$P(G_2=W\&G_1=W)=P(G_1=W)*P(G_2=W|G_1=W)=0.4*0.2=0.08$

d) The variable X can take values 0, 1 and 2.

X=0 is when both games are lost. This happens with probability P=0.42.

X=2 is when both games are won. This happens with probability P=0.08.

X=1 is when one game is won and the other is lost. This happens with probability P=1-0.42-0.08=0.50.

Then the table of probabilities become:

X | P(X)

------------------

0 | 0.42

1 | 0.50

2 | 0.08

e) The expected value is:

$E(x)=\sum p_ix_i=0.42*0+0.50*1+0.08*2=0.00+0.50+0.16=0.66$

The variance and standard deviation of x are:

$V(x)=\sum p_i(x_i-E(x))^2\\\\V(x)=0.42(0-0.66)^2+0.50(1-0.66)^2+0.08(2-0.66)^2\\\\V(x)=0.42*0.4356+0.50*0.1156+0.08*1.7956\\\\V(x)=0.183+0.058+0.144=0.385\\\\\\\sigma=\sqrt{V(x)}=\sqrt{0.385}=0.62$