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3 years ago

Help me plezzzzzzzzzzzzzzzzzz

Mathematics

1 answer:

alexdok [17]3 years ago

8 0

31. There are C(5, 2) = 10 ways to choose 2 colors from a group of 10 colors if you don't care about the order. (Here, we treat blue background with violet letters as being indistinguishable from violet background with blue letters.)

Only one of those 10 pairs is "B and V", so the probability is 1/10.
a) P(B and V) = 10%

32. The 12 inch dimension on the figure is 0 inches for the cross section. The remaining dimensions of the cross section are
c) 5 in. × 4 in.

_____
C(n, k) = n!/(k!·(n-k)!)
C(5, 2) = 5!/(2!·3!) = 5·4/(2·1) = 10

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4 times as much as 3 is blank

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Step-by-step explanation:

4 times 3 is 12.

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2 years ago

Two buses leave towns 1631km apart at the same time and travel toward each other. one bus travels 17 /kmh slower than the other.

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3 years ago

A sample of 100 cars driving on a freeway during a morning commute was drawn, and the number of occupants in each car was record

makkiz [27]

Answer:

$E(X)=1*0.74 +2*0.1 +3*0.11+ 4*0.03 +5*0.02=1.49$

$Var(X)=E(X^2)-[E(X)]^2 =3.11-(1.49)^2 =0.8899$

$Sd(X)=\sqrt{Var(X)}=\sqrt{0.8899}=0.943$

Step-by-step explanation:

For this case we have the following data given:

X 1 2 3 4 5

F 74 10 11 3 2

The total number of values are 100, so then we can find the empirical probability dividing the frequency by 100 and we got the followin distribution:

X 1 2 3 4 5

P(X) 0.74 0.10 0.11 0.03 0.02

Previous concepts

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.

Solution to the problem

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:

$E(X)=1*0.74 +2*0.1 +3*0.11+ 4*0.03 +5*0.02=1.49$

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:

$E(X^2)=1^2 *0.74 +2^2 *0.1 +3^2 *0.11 +4^2 0.03 +5^2 *0.02=3.11$

Then we can find the variance with the following formula:

$Var(X)=E(X^2)-[E(X)]^2 =3.11-(1.49)^2 =0.8899$

And then the standard deviation would be given by:

$Sd(X)=\sqrt{Var(X)}=\sqrt{0.8899}=0.943$

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3 years ago

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Answer:

c) 3,000

Step-by-step explanation:

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2 years ago