Answer:
288xy
Step-by-step explanation:
First, you multiply 12 by 24 and you get 288. Next, you can't forget the variables, so you add those to the end and get, 288xy.
P(volleyball and baseball) = 4/200 x 100 = 2%
P(either volleyball or baseball) = P(volleyball ∪ baseball) = P(volleyball) + P(baseball) - P(volleyball and baseball) = 12% + 15% - 2% = 25%.
25% play either volleyball or baseball.
Answer: The charge was right.
Step-by-step explanation:
If he charged $18 per hour, it means he charged $18 for 60 minutes. He worked for 2 hours 15 minutes which is (60 ×2) + 15 = 135 minutes. For 135 mins, (135 ×18)÷ 60 = 40.5.
He drove 21 miles to his house and 21 miles back. That is 21×2= 42. And for $0.27 = $11.34.
Adding the costs, 40.5 + 11.34 = $51.84
Answer:

In order to find the variance we need to find first the second moment given by:

And replacing we got:

The variance is calculated with this formula:
![Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075](https://tex.z-dn.net/?f=%20Var%28X%29%20%3D%20E%28X%5E2%29%20-%5BE%28X%29%5D%5E2%20%3D%200.33%20-%280.15%29%5E2%20%3D%200.3075)
And the standard deviation is just the square root of the variance and we got:

Step-by-step explanation:
Previous concepts
The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.
The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).
Solution to the problem
LEt X the random variable who represent the number of defective transistors. For this case we have the following probability distribution for X
X 0 1 2 3
P(X) 0.92 0.03 0.03 0.02
We can calculate the expected value with the following formula:

And replacing we got:

In order to find the variance we need to find first the second moment given by:

And replacing we got:

The variance is calculated with this formula:
![Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075](https://tex.z-dn.net/?f=%20Var%28X%29%20%3D%20E%28X%5E2%29%20-%5BE%28X%29%5D%5E2%20%3D%200.33%20-%280.15%29%5E2%20%3D%200.3075)
And the standard deviation is just the square root of the variance and we got:
