Understanding Joint Density Functions: Solving for Unknown Parameters

In summary, the conversation discusses finding the value of a in the joint density function given certain boundaries and the need for the total probability to equal 1. The conversation also briefly mentions the use of marginal functions and covariance in this problem.
  • #1
wuid
40
0
it seems that i can't understand the boundaries...
the joint density function:

f(u,v)= a , u^2 <= v <= 1
0 , else

find a

i just don't know how to start.
any help ?
thx
 
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  • #2
welcome to pf!

hi wuid! welcome to pf! :smile:

(try using the X2 button just above the Reply box :wink:)

let's see :rolleyes: … that's a shelf of height a whose shape is a rectangle with a parabola cut out of it …

ok, you need it to have total probability of 1 :smile:
 
  • #3
hi !
thx for the quick reply ,

let's see if i got u ,

[itex]\int^{1}_{-1}\int^{1}_{u^{2}}advdu=1[/itex]

so [itex]a=\frac{3}{4}[/itex]

is that right ?
 
  • #4
looks good! :smile:
 
  • #5
can you please guide me with two more section in this problem ,
related to marginal functions & covariance ?

and i'll leave you for good :)

i
 
  • #6
i'm not much good at statistics :redface:

can you start a new thread? :smile:
 
  • #7
o.k i'll start a new one later.

first i'll try harder... :)
 

Related to Understanding Joint Density Functions: Solving for Unknown Parameters

1. What is a joint density problem?

A joint density problem is a statistical problem that involves finding the probability density function of two or more random variables.

2. How do you solve a joint density problem?

To solve a joint density problem, you need to first determine the joint probability density function of the given variables, and then integrate it over the desired range to find the probability of the event.

3. What is the difference between a joint density problem and a marginal density problem?

A joint density problem involves finding the probability density function of two or more variables together, while a marginal density problem involves finding the probability density function of a single variable from the joint density function.

4. What are some common applications of joint density problems?

Joint density problems are commonly used in fields such as finance, economics, and engineering to model and analyze complex systems and make predictions about future outcomes.

5. Are there any limitations to joint density problems?

Joint density problems assume that the given variables are independent of each other, which may not always be the case in real-world scenarios. Additionally, the accuracy of the results depends on the accuracy of the assumed distributions and parameters.

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