Answer:
these are the answers of the questions x<-2 or x<2
Answer:
1 < x < 4 . . . . {x | x < 4 <u>and</u> x > 1}
Step-by-step explanation:
We want to write the answer as a compound inequality, if possible. As it is written, we can solve each separately.
x + 1 < 5
x < 4 . . . . . . . subtract 1
__
x -4 > -3
x > 1 . . . . . . . add 4
So, the solution is ...
(x < 4) ∩ (x > 1) . . . . . . the intersection of the two solutions
As a compound inequality, this is written ...
1 < x < 4
_____
<em>Comment on the problem</em>
The two answer choices shown don't make any sense. You might want to have your teacher demonstrate the solution to this problem.
Hey there!
On this problem, we have to combine like terms. A like term in this sense doesn't have to have the same coefficient, but it has to have the same variable.
Our like terms are 2m and 4m, along with 3 and 5.
When we add 2m and 4m we get 6m, and when we add 5 and 3 we get eight.
Notice how 5 and three are like terms because they're both whole numbers and don't have any variables.
Your solution is 6m + 8.
My advice to you is pay attention to your like terms and don't mix them up. A strategy is to underline like terms in the same color.
Hope this helps!
Answer:
The expected cost is 152
Step-by-step explanation:
Recall that since Y is uniformly distributed over the interval [1,5] we have the following probability density function for Y
if 
and 0 othewise. (To check this is the pdf, check the definition of an uniform random variable)
Recall that, by definition
Also, we are given that 
. Recall the following properties of the expected value. If X,Y are random variables, then
Then, using this property we have that ![E[C] = 50+3E[Y]+ 9E[Y^2]](https://tex.z-dn.net/?f=E%5BC%5D%20%3D%2050%2B3E%5BY%5D%2B%209E%5BY%5E2%5D)
.
Thus, we must calculate E[Y] and E[Y^2].
Using the definition, we get that
![E[Y] = \int_{1}^{5}\frac{y}{4} dy =\frac{1}{4}\left\frac{y^2}{2}\right|_{1}^{5} = \frac{25}{8}-\frac{1}{8} = 3](https://tex.z-dn.net/?f=E%5BY%5D%20%3D%20%5Cint_%7B1%7D%5E%7B5%7D%5Cfrac%7By%7D%7B4%7D%20dy%20%3D%5Cfrac%7B1%7D%7B4%7D%5Cleft%5Cfrac%7By%5E2%7D%7B2%7D%5Cright%7C_%7B1%7D%5E%7B5%7D%20%3D%20%5Cfrac%7B25%7D%7B8%7D-%5Cfrac%7B1%7D%7B8%7D%20%3D%203)
![E[Y^2] = \int_{1}^{5}\frac{y^2}{4} dy =\frac{1}{4}\left\frac{y^3}{3}\right|_{1}^{5} = \frac{125}{12}-\frac{1}{12} = \frac{31}{3}](https://tex.z-dn.net/?f=E%5BY%5E2%5D%20%3D%20%5Cint_%7B1%7D%5E%7B5%7D%5Cfrac%7By%5E2%7D%7B4%7D%20dy%20%3D%5Cfrac%7B1%7D%7B4%7D%5Cleft%5Cfrac%7By%5E3%7D%7B3%7D%5Cright%7C_%7B1%7D%5E%7B5%7D%20%3D%20%5Cfrac%7B125%7D%7B12%7D-%5Cfrac%7B1%7D%7B12%7D%20%3D%20%5Cfrac%7B31%7D%7B3%7D)
Then
