Answer:
a) The expected value is given by:
![E(X) =\frac{a+b}{2}= \frac{10+12}{2}= 11](https://tex.z-dn.net/?f=%20E%28X%29%20%3D%5Cfrac%7Ba%2Bb%7D%7B2%7D%3D%20%5Cfrac%7B10%2B12%7D%7B2%7D%3D%2011)
The variance is given by:
![Var(X) = \frac{(b-a)^2}{12}= \frac{(12-10)^2}{12}= 0.3333](https://tex.z-dn.net/?f=%20Var%28X%29%20%3D%20%5Cfrac%7B%28b-a%29%5E2%7D%7B12%7D%3D%20%5Cfrac%7B%2812-10%29%5E2%7D%7B12%7D%3D%200.3333)
And the standard deviation is just the square root of the variance and we got:
![Sd(x) = \sqrt{0.3333}= 0.5774](https://tex.z-dn.net/?f=%20Sd%28x%29%20%3D%20%5Csqrt%7B0.3333%7D%3D%200.5774)
b) ![P(X](https://tex.z-dn.net/?f=%20P%28X%3C11%29)
And we can use the cumulative distribution function given by:
![F(x) = \frac{x-a}{b-a}, a \leq x \leq b](https://tex.z-dn.net/?f=%20F%28x%29%20%3D%20%5Cfrac%7Bx-a%7D%7Bb-a%7D%2C%20a%20%5Cleq%20x%20%5Cleq%20b)
And using this function we got:
![P(X](https://tex.z-dn.net/?f=%20P%28X%3C11%29%20%3D%20%5Cfrac%7B11-10%7D%7B12-10%7D%3D%200.50)
c) ![P(X>10.5)](https://tex.z-dn.net/?f=%20P%28X%3E10.5%29)
And using the complement rule and the cumulative distribution function we got:
![P(X>10.5)= 1-P(X](https://tex.z-dn.net/?f=%20P%28X%3E10.5%29%3D%201-P%28X%3C10.5%29%20%3D%201-%5Cfrac%7B10.5-10%7D%7B12-10%7D%3D%201-0.25%20%3D%200.75)
Step-by-step explanation:
For this case we define the random variable X=quantity put in each bag , and we know that the distribution for X is given by:
![X \sim Unif (a= 10, b =12)](https://tex.z-dn.net/?f=%20X%20%5Csim%20Unif%20%28a%3D%2010%2C%20b%20%3D12%29)
Part a
The expected value is given by:
![E(X) =\frac{a+b}{2}= \frac{10+12}{2}= 11](https://tex.z-dn.net/?f=%20E%28X%29%20%3D%5Cfrac%7Ba%2Bb%7D%7B2%7D%3D%20%5Cfrac%7B10%2B12%7D%7B2%7D%3D%2011)
The variance is given by:
![Var(X) = \frac{(b-a)^2}{12}= \frac{(12-10)^2}{12}= 0.3333](https://tex.z-dn.net/?f=%20Var%28X%29%20%3D%20%5Cfrac%7B%28b-a%29%5E2%7D%7B12%7D%3D%20%5Cfrac%7B%2812-10%29%5E2%7D%7B12%7D%3D%200.3333)
And the standard deviation is just the square root of the variance and we got:
![Sd(x) = \sqrt{0.3333}= 0.5774](https://tex.z-dn.net/?f=%20Sd%28x%29%20%3D%20%5Csqrt%7B0.3333%7D%3D%200.5774)
Part b
For this case we want this probability:
![P(X](https://tex.z-dn.net/?f=%20P%28X%3C11%29)
And we can use the cumulative distribution function given by:
![F(x) = \frac{x-a}{b-a}, a \leq x \leq b](https://tex.z-dn.net/?f=%20F%28x%29%20%3D%20%5Cfrac%7Bx-a%7D%7Bb-a%7D%2C%20a%20%5Cleq%20x%20%5Cleq%20b)
And using this function we got:
![P(X](https://tex.z-dn.net/?f=%20P%28X%3C11%29%20%3D%20%5Cfrac%7B11-10%7D%7B12-10%7D%3D%200.50)
Part c
For this case we want this probability:
![P(X>10.5)](https://tex.z-dn.net/?f=%20P%28X%3E10.5%29)
And using the complement rule and the cumulative distribution function we got:
![P(X>10.5)= 1-P(X](https://tex.z-dn.net/?f=%20P%28X%3E10.5%29%3D%201-P%28X%3C10.5%29%20%3D%201-%5Cfrac%7B10.5-10%7D%7B12-10%7D%3D%201-0.25%20%3D%200.75)