+ Reply to Thread
Results 1 to 4 of 4

Thread: Three (or more) normally distributed variables

  1. #1
    Points: 1,252, Level: 19
    Level completed: 52%, Points required for next Level: 48

    Posts
    13
    Thanks
    1
    Thanked 0 Times in 0 Posts

    Smile Three (or more) normally distributed variables




    Hi
    I have three variables, X, Y and Z with all different means but same standard deviation. All are normally distributed. It could be four in some cases.

    How can I calculate probability that a random observation on X will be > than Y and Z?

    I appreciate any kind of help. I will perform test in Excel so extra good with some excel tip.

  2. #2
    Points: 1,252, Level: 19
    Level completed: 52%, Points required for next Level: 48

    Posts
    13
    Thanks
    1
    Thanked 0 Times in 0 Posts

    Re: Three (or more) normally distributed variables

    Thinking of it.. variables are more likely to be Poisson distributed.. Could I apply Skellam distribution here in some way?

    I dont have observations for these variables. X, Y and Z are estimated number of goals in three different independent football matches. I would like to calculate probability that it will be most goals in Match X.

  3. #3
    Devorador de queso
    Points: 95,781, Level: 100
    Level completed: 0%, Points required for next Level: 0
    Awards:
    Posting AwardCommunity AwardDiscussion EnderFrequent Poster
    Dason's Avatar
    Location
    Tampa, FL
    Posts
    12,933
    Thanks
    307
    Thanked 2,629 Times in 2,245 Posts

    Re: Three (or more) normally distributed variables

    If they have different means but the same standard deviation how could they be poisson?
    I don't have emotions and sometimes that makes me very sad.

  4. #4
    Points: 1,252, Level: 19
    Level completed: 52%, Points required for next Level: 48

    Posts
    13
    Thanks
    1
    Thanked 0 Times in 0 Posts

    Re: Three (or more) normally distributed variables


    that makes of course no sense

    What I am trying to do is to estimate probability that Match A will contain most goals among Match A, B and C.

    My first idea was to see number of goals as normally distributed with estimated variance from 4K matches. Match A, B and C will have different estimations for number of goals.

    The variable of interest here is number of Goals, X. That will come from three different populations, match A, B and C.

    That is probably a better way to describe what im trying to do. But how should I see X distributed? And how can I calculate probability that Match A will contain most goals?

    Mean for goals scored in 4K matches = 2.74 and variance = 2.9. So I dont think there will be any problem with over dispersion, in this case if I view X as Poission distributed.

+ Reply to Thread

           




Posting Permissions

  • You may not post new threads
  • You may not post replies
  • You may not post attachments
  • You may not edit your posts






Advertise on Talk Stats