Determining the distribution function

In summary, the problem is that I'm not integrating correctly and I'm not sure where I'm going wrong.
  • #1
shan
57
0
I've gotten a weird answer after doing the problem but I'm stuck as to where I messed up.

The density function is this:
[tex]f_{X} (x) = \frac{1}{6}x[/tex] for [tex]0<x\leq2[/tex]
[tex] = \frac{1}{3}(2x-3)[/tex] for 2<x<3
and 0 otherwise

And the question is to find the distribution function.

So integrating for the first part from 0 to x:
[tex]\int \frac{1}{6}u du = \frac {1}{6} \frac{x^2}{2} = \frac{x^2}{16}[/tex]
for 0<x<=2

I have a big problem with the second, part. This is what I did (integrating from 2 to x):
[tex]\int \frac{1}{3} (2u-3) du = \frac{1}{3} [u^2-3u] = \frac{1}{3} (x^2-3x - (2^2-6)) = \frac{x^2}{3} - x + \frac{2}{3}[/tex]
for 2<x<3

I know my answer for the second part is wrong as when x=2, the distribution function = 0 and when x=3, the distribution function = 2/3. But the distribution shouldn't be broken up like that at x=2 and supposedly at x=3, it should = 1. So did I forget to do something to the end points or did I not integrate properly?
 
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  • #2
The distribution function is given by:

[tex]F_X(x) := \int_{-\infty}^x f_X(x) \, dx[/tex]

So when you computed [itex]\int_2^x f_X(x) \, dx[/itex], you computed the wrong thing, and there's no reason you should have gotten the right answer.

P.S. 6*2 is not 16.
 
  • #3
Hurkyl said:
P.S. 6*2 is not 16.
whoops sorry, typo :blushing: that first part is
[tex]\int_0^x \frac{1}{6}u du = \frac {1}{6} \frac{x^2}{2} = \frac{x^2}{12}[/tex]

Hurkyl said:
The distribution function is given by:

[tex]F_X(x) := \int_{-\infty}^x f_X(x) \, dx[/tex]

So when you computed [itex]\int_2^x f_X(x) \, dx[/itex], you computed the wrong thing, and there's no reason you should have gotten the right answer.
which shows I don't really understand what I'm doing but now that you mentioned it...

is the second part then given by [tex]\int_0^2 \frac{1}{6}u du + \int_2^x \frac{1}{3} (2u-3) du[/tex]? ie I forgot to add the first part of f(x)?
 
  • #4
Right. Of course, there should also be a [itex]\int_{-\infty}^0 f_X(u) \, du[/itex] component as well. (But you know it's zero, so I suppose that's why you left it out)
 
  • #5
Thank you very much for your help :)
 

Related to Determining the distribution function

What is a distribution function?

A distribution function is a mathematical function that describes the probability of a random variable taking on a specific value or falling within a certain range of values. It is used to model the behavior of a data set and can provide insights into the characteristics and patterns of the data.

What are the types of distribution functions?

There are several types of distribution functions, including normal, uniform, exponential, and binomial. Each type is characterized by its own unique shape and set of parameters that determine the probability of different outcomes.

How is a distribution function determined?

A distribution function can be determined by analyzing a data set and fitting it to a specific type of distribution using statistical methods. This involves calculating the mean, standard deviation, and other measures of central tendency and using them to determine the most appropriate distribution for the data.

What is the purpose of determining a distribution function?

The purpose of determining a distribution function is to gain a better understanding of the data and its underlying patterns. It can also be used to make predictions and inform decision-making in various fields such as economics, finance, and biology.

What are some common misconceptions about distribution functions?

One common misconception about distribution functions is that they are limited to certain types of data or only applicable to certain situations. In reality, distribution functions can be used to model a wide range of data sets and can provide valuable insights in various fields of study. Another misconception is that the shape of a distribution function is always symmetrical, when in fact, many real-world data sets exhibit asymmetrical distributions.

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