Uniform Distribution Homework: Mean and Variance of Profit Y

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In summary, the industrial robot is in operation for aproximately 2/3 of the time during a 40 hour work week and the profit for the week is y=-176/3.
  • #1
Mdhiggenz
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Homework Statement



The proportion of time x that an industrial robot is in operation during a 40 hour work week is a random variable wth probability density function
f(x)= 2x 0≤x≤1

I already found my E(x) to be 2/3 " Mean" and V(x) to be 1/18 " variance"

Here is where things get confusing for me.

For the robot under study, the profit Y for a week is given by

Y=200*x-60

Find E(Y) and V(Y).

So I found E(Y) to be just y=200(E(x))-60

which makes sense.

But for V(Y)

we have to ignore the constant and sqareroot the first term so it would be

V(Y)=v[200x-60]=2002*v(x) "ignoring the constant"=2002*1/18

I don't understand the logic to computing the variance. Why would we ignore the constant and just square the first term?

Thanks



Homework Equations





The Attempt at a Solution

 
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  • #2
I presume that you know that [itex]E(x)= \int xf(x)dx[/itex] and [itex]V= \int (x- x_0)^2f(x)dx[/itex]. Given that y= 2x- 60, yes, you can just put E(x) in for x and get [itex]E(y)= 2(2/3)- 60= 4/3- 60= -176/3[/itex] or -58 and 2/3.

If you were to replace x by 2x- 60 and [itex]E(x)[/itex] by that mean, you should be able to see that in [itex]((2x- 60)- (4/3- 60))^2[/itex] you can cancel the two "-60" terms. to find the variation of Y, integrate [itex](2x- 4/3)^2[/itex].
 
  • #3
Mdhiggenz said:
I don't understand the logic to computing the variance. Why would we ignore the constant and just square the first term?
In general, if ##y = ax + b##, then ##E[y] = aE[x] + b##, so
$$\begin{align}
y - E[y] &= (ax + b) - (aE[x] + b)\\
&= ax - aE[x]\\
&= a(x - E[x])
\end{align}$$
Therefore,
$$\begin{align}
var(y) &= E\bigl[(y - E[y])^2\bigr]\\
&= E\bigl[\bigl(a(x - E[x])\bigr)^2]\\
&= E\bigl[a^2(x - E[x])^2\bigr]\\
&= a^2E\bigl[(x - E[x])^2\bigr]\\
&= a^2 var(x)
\end{align}$$
 

FAQ: Uniform Distribution Homework: Mean and Variance of Profit Y

1. What is a uniform distribution?

A uniform distribution is a type of probability distribution where all outcomes have an equal chance of occurring. This means that the probability of any single outcome is the same as any other outcome.

2. How is a uniform distribution used in the context of profit Y?

In the context of profit Y, a uniform distribution can be used to model the potential profits of a business or investment. This can help calculate the expected value, or mean, of profit Y and the variability, or variance, of profit Y.

3. What is the formula for calculating the mean of a uniform distribution?

The formula for calculating the mean of a uniform distribution is (a + b)/2, where a is the lower limit of the distribution and b is the upper limit. In the case of profit Y, this formula would be used to calculate the expected value of profit Y.

4. How is the variance of a uniform distribution calculated?

The variance of a uniform distribution is calculated using the formula (b-a)^2/12, where a is the lower limit and b is the upper limit of the distribution. This formula can be used to determine the variability of profit Y.

5. Can a uniform distribution accurately represent real-life scenarios?

In some cases, a uniform distribution can accurately represent real-life scenarios, such as when all outcomes have an equal chance of occurring. However, in many situations, other types of distributions may be more appropriate to model real-life data, as they can better account for variations and patterns. It is important to carefully consider the characteristics of the data before deciding on which distribution to use.

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