Probability density and continuous variables

In summary, the tank should hold at least 550 liters of fuel so that the probability of it being emptied within a week is less than 5%.
  • #1
peripatein
880
0
Hi,
I would certainly appreciate it if you could please confirm the result I obtained to the following Statistics problem.

Homework Statement


A tank is supplied with fuel once a week. If the fuel (in thousands of liters) that the station sells in a week is a random variable which is distributed with the following density:
fx(x) = c(1-x)4 for 0≤x≤1 and 0 otherwise
what ought to be the capacity of the tank so that the probability that it is emptied within a week is less than 5%?

Homework Equations





The Attempt at a Solution


Since x is a random variable, with continuous distribution, it must fulfill the following conditions:
f(x)≥0 and ∫f(x)dx between 0 and 1 must be equal to 1. Hence, c = 5.
I then found F(x), the cumulative distribution, to be:
0 for x<0, x5 for 0≤x≤1, and 1 for x>1.
Which inequality must now be written in order to assure the required condition? Is it x5<0.05, yielding 550 liters?
 
Physics news on Phys.org
  • #2
peripatein said:
Hi,
I would certainly appreciate it if you could please confirm the result I obtained to the following Statistics problem.

Homework Statement


A tank is supplied with fuel once a week. If the fuel (in thousands of liters) that the station sells in a week is a random variable which is distributed with the following density:
fx(x) = c(1-x)4 for 0≤x≤1 and 0 otherwise
what ought to be the capacity of the tank so that the probability that it is emptied within a week is less than 5%?

Homework Equations


The Attempt at a Solution


Since x is a random variable, with continuous distribution, it must fulfill the following conditions:
f(x)≥0 and ∫f(x)dx between 0 and 1 must be equal to 1. Hence, c = 5.
I then found F(x), the cumulative distribution, to be:
0 for x<0, x5 for 0≤x≤1, and 1 for x>1.
Which inequality must now be written in order to assure the required condition? Is it x5<0.05, yielding 550 liters?

Your work up until the last couple of lines is fine, but your guess of 550 liters doesn't pass the snicker test. After all, if he sold all his gas it would be 1000 liters. He usually doesn't sell all of it, so he could use a smaller tank if he is willing to run out less than 5% of the time. How much doesn't he exceed selling 95% of the time?
 
Last edited:
  • #3
I am not sure I follow your reasoning. Would you please clarify?
 
  • #4
If I am not mistaken, the answer should be 1-(0.05)^(0.2) = 450 liters. But why?
 
  • #5
Let's step back a bit. I overlooked that your cumulative distribution function of ##x^5## doesn't seem to be correct. How did you get that?
 
  • #6
I integrated 5(1-x)^4 between 0 and x.
 
  • #7
My apologies, it should have been 1-(1-x)^5. How shall I proceed?
 
Last edited:
  • #8
peripatein said:
My apologies, it should have been 1-(1-x)^5. How shall I proceed?

That's better. What value of X would assure that you don't run out 95% of the time? That may lead you to one of your previous answers, but hopefully now you will see why.
 
  • #9
I see where this is going and still am unable to fathom why it shouldn't be 1-(1-x)^5 = 0.05? I mean, let's say the capacity of the tank is r gallons (or liters). If r gallons/liters are then sold in a given week, the tank is exhausted, which is the desired outcome merely 5% of times. Right? Ergo, I would think the equation should be 1-(1-r)^5 = 0.05, instead of 1-(1-r)^5 = 0.95. Now, I KNOW I am wrong, but cannot understand why. Would you please care to explain?
 
  • #10
You want the probability that you could have sold more than your new tank holds to be small (.05). That means you want the probability that the amount sold is less than equal to your new tank capacity to be large (.95). That's F(x)=.95. Does that help?
 
  • #11
It does. Thank you!
 

FAQ: Probability density and continuous variables

1. What is probability density?

Probability density is a concept in statistics that refers to the likelihood of a continuous variable falling within a certain range of values. It is represented by a probability distribution curve, where the area under the curve represents the probability of a variable falling within a specific range.

2. How is probability density different from probability?

Probability density is a measure of the likelihood of a continuous variable, whereas probability is a measure of the likelihood of a discrete event. Probability can take on values between 0 and 1, while probability density can take on any positive value. Additionally, probability density is used for continuous variables, while probability is used for discrete variables.

3. What is a continuous variable?

A continuous variable is a type of numerical variable that can take on any value within a certain range. This means that there are infinite possible values between two points on a continuous scale. Examples of continuous variables include height, weight, and time.

4. How is probability density calculated?

Probability density is calculated by taking the derivative of the cumulative distribution function (CDF) of a continuous variable. The CDF is a function that gives the probability of a variable being less than or equal to a certain value. By taking the derivative, we can find the probability density at a specific point on the distribution curve.

5. What is the relationship between probability density and the normal distribution?

The normal distribution, also known as the bell curve, is a common probability distribution that is often used to model continuous variables. The shape of the normal distribution curve is determined by its mean and standard deviation, which can also be used to calculate the probability density at any given point on the curve. In fact, the normal distribution is often used as a reference for other probability distributions, as many real-world phenomena can be approximated by the normal distribution.

Back
Top