Distribution Function Of X Help

In summary, the distribution function of X is given by f(x) = 0 if x <= 5, f(x) = x/10 - 1/2 if 5 < x <= 15, and f(x) = 1 if x > 15. The task is to find the probability that the value of X falls between 6 and 12. In order to do this, we need to find the integral of f(x) from 6 to 12, which is equal to F(12) - F(6). By definition, the probability distribution function is equal to the probability of X being less than a certain value. However, the given equation is quite confusing and difficult to understand, especially for
  • #1
mircat
This is what I have:

Let the distribution function of X be given by
f(x) = 0, if x < (or equal to) 5
f(x) = x/10 - 1/2, if 5<x<(or equal to) 15
f(x) = 1, if x>15

Find p(6<x<12)

Ok, everyone. I need major help. I have no clue where to even begin. I have searched the web for help w/o luck. I need help in "layman's terms" as I do not understand any of this stuff. (note my other post on die rolls)LOL This equation is due tonight. Please, someone help me. Have to pass this class. :cry:
 
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  • #2
I bet the answer (or at least a good starting point) lies in the definition of a probability distribution function, if you look it up in your textbook!
 
  • #3
Lord, Hurky, I have. I have searched online, too. The book is a joke. No where in it is even a close example of one like this. I am still searching. Not going to give up just yet. :eek:)
 
  • #4
Answer

Let say X is a continuous random variable with probability density function (or pdf) f(x), and cumulative density function (or distribution function df) F(x). By definition 0<=F(x)<=1, and lim F(x) as x goes to minus or infinity is 0 and 1 respectively. By the Fundamental Theorem of Calculus, f(x)=F'(x), then the integral of f(x)dx from a to b is equal to F(b)-F(a) (where a and b are constants within the interval where f(x) is defined).
In your case, just take the integration of F'(x) = d(x/10 - 1/2) = 1/10, with respect to x from 6 to 12. Or, just evaluate and compute F(12)-F(6)=[(12/10)-1/2] - [(6/10)-1/2].

I think this may work.
 
Last edited:
  • #6
PS - only one week left, so I won't be pestering all you guys much longer! :smile: I really and truly appreciate everyone's help!
 
  • #7
Don't you have this definition of the probability distribution function:

f(a) := P(X < a)?
 
  • #8
I have seen so many of these "formulas" it boggles my poor mind. This last week's assignment is more of the same type...density functions / continuous distribution functions. I just soooo don't get it. I really don't. I see an example from a lecture (written) then the problem I am given to do is nothing like it at all. An exaggeration is: f(x) = a x b + m (x)2 = v is what I am seeing in a lecture, but then I am told to solve the chemical equation for Tide. LOL Make sense? One paragraph shows Xs, Fs, maybe a Y - then the next one adds an E, H - w/o telling me why. Where'd the E and H come from? LOL I am trying to keep a sense of humor about all of this. I will let you know the final grade when it's over. :eek:) Oh, I see a "t" on this week's lecture. ROFL! :eek:

pami

ps - Hurky, did I tell you it's been almost 20 years since I've seen this stuff. I didn't even have to take Calculus/Stat/Prob in high school...so this is all foreign to me. :eek:)
 

1. What is a distribution function?

A distribution function, also known as a cumulative distribution function, is a mathematical function that describes the probability that a random variable takes on a value less than or equal to a specific value. In other words, it gives us the cumulative probability of a random variable being less than or equal to a given value.

2. How is a distribution function different from a probability density function?

A distribution function gives us the cumulative probability of a random variable being less than or equal to a given value, while a probability density function gives us the probability of a random variable taking on a specific value. In other words, a distribution function takes into account all values up to a certain point, while a probability density function focuses on a specific value.

3. What are the properties of a distribution function?

There are three main properties of a distribution function: 1) it is a non-decreasing function, meaning that as the input value increases, the output value also increases or stays the same, 2) it ranges from 0 to 1, as it represents probabilities, and 3) it approaches 0 as the input value approaches negative infinity and approaches 1 as the input value approaches positive infinity.

4. How is the distribution function used in statistics?

The distribution function is used in statistics to calculate probabilities and make inferences about a population based on a sample. It is used to find the probability of a random variable falling within a certain range, and it also helps in determining the likelihood of a given sample being representative of the entire population.

5. Can the distribution function be used for any type of data?

Yes, the distribution function can be used for any type of data, as long as it follows a certain distribution. Some common distributions include the normal distribution, binomial distribution, and exponential distribution. It is important to identify the appropriate distribution for the data in order to accurately use the distribution function.

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