Answer:
The probability that the demand will exceed 190 cfs during the early afternoon on a randomly selected day is
![P(Y>190)=\frac{1}{e^{(19)/(10)}}\approx 0.1496](https://img.qammunity.org/2020/formulas/mathematics/college/m538wu28z8kgd64rzcp6kcnisj9y5fugyn.png)
Explanation:
Let Y be the water demand in the early afternoon.
If the random variable Y has density function f (y) and a < b, then the probability that Y falls in the interval [a, b] is
![P(a\leq Y \leq b)=\int\limits^a_b {f(y)} \, dy](https://img.qammunity.org/2020/formulas/mathematics/college/5jknmqwbbddky3zwelncs5hht444u9n1bh.png)
A random variable Y is said to have an exponential distribution with parameter
if and only if the density function of Y is
![f(y)=\left \{ {{(1)/(\beta)e^{-(y)/(\beta) }, \quad{0\:\leq \:y \:\leq \:\infty} } \atop {0}, \quad elsewhere} \right.](https://img.qammunity.org/2020/formulas/mathematics/college/nj83la1cuhchvkb1p269hkfgmo7uq3kdqp.png)
If Y is an exponential random variable with parameter β, then
mean = β
To find the probability that the demand will exceed 190 cfs during the early afternoon on a randomly selected day, you must:
We are given the mean = β = 100 cubic feet per second
![P(Y>190)=\int\limits^(\infty)_(190) {(1)/(100)e^(-y/100) } \, dy](https://img.qammunity.org/2020/formulas/mathematics/college/reekrvjow5ddclxcy0h3cme3fxrgtqt23u.png)
Compute the indefinite integral
![\int (1)/(100)e^{-(y)/(100)}dy](https://img.qammunity.org/2020/formulas/mathematics/college/z9sj9uaki67q6m30atcc5zq2hvq9i4qu9v.png)
![(1)/(100)\cdot \int \:e^{-(y)/(100)}dy\\\\\mathrm{Apply\:u \:substitution}\:u=-(y)/(100)\\\\(1)/(100)\cdot \int \:-100e^udu\\\\(1)/(100)\left(-100\cdot \int \:e^udu\right)\\\\(1)/(100)\left(-100e^u\right)\\\\\mathrm{Substitute\:back}\:u=-(y)/(100)\\\\(1)/(100)\left(-100e^{-(y)/(100)}\right)\\\\-e^{-(y)/(100)}](https://img.qammunity.org/2020/formulas/mathematics/college/zesuwwks7ly2vw2wmrdl3a0fott3jrzi07.png)
Compute the boundaries
![\int _(190)^(\infty \:)(1)/(100)e^{-(y)/(100)}dy=0-\left(-\frac{1}{e^{(19)/(10)}}\right)](https://img.qammunity.org/2020/formulas/mathematics/college/yprqg27j9a4szq0tjb2013fuzri3bjfecn.png)
![\int _(190)^(\infty \:)(1)/(100)e^{-(y)/(100)}dy=\frac{1}{e^{(19)/(10)}}\approx 0.1496](https://img.qammunity.org/2020/formulas/mathematics/college/l8lle06tjme7b5vk259p9sonv7aqafayxw.png)
The probability that the demand will exceed 190 cfs during the early afternoon on a randomly selected day is
![P(Y>190)=\frac{1}{e^{(19)/(10)}}\approx 0.1496](https://img.qammunity.org/2020/formulas/mathematics/college/m538wu28z8kgd64rzcp6kcnisj9y5fugyn.png)