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Mathematics 21 Online
OpenStudy (anonymous):

Let the discrete random variable X have probability mass function p(x) such that p(x) =1/n x= a+1, a+2,a+3,...,a+n =0 elsewhere what is the mean of this distribution?

hartnn (hartnn):

the formula for mean is \[\sum_{a+1}^{a+n}x*p(x)\] can u find this?

OpenStudy (anonymous):

not sure...would i need to try simplify the sum first?

hartnn (hartnn):

u need to put the value of p(x) first.,then evaluate the summation ever evaluated the summation??

OpenStudy (anonymous):

like i wouldnt know how to evaluate something with\[\sum_{a+1}^{a+n}\]

OpenStudy (anonymous):

\[\sum_{a+1}^{a+n} x*1/n ?\]

hartnn (hartnn):

there are formulae to evaluate the summation,like \[\sum_{1}^{n}1=n\] and \[\sum_{1}^{n}n=n*\frac{(n+1)}{2}\]

hartnn (hartnn):

u made that substitution correct.... now 'n' is a constant for summation,because u are summing w.r.t x,so u can bring out n like this \[\frac{1}{n}\sum_{a+1}^{a+n}x\] got this?

OpenStudy (anonymous):

yes i agree. unfortunately the a+1 part of the sum is still a little bit confusing for me...

hartnn (hartnn):

ok,but till here you understood,right? i will go further and substitute y=x-a to get rid of a+1 so now lower limit changes from x=a+1 to y=1 got this?if yes,then tell me what would upper limit x=a+n change to?

OpenStudy (anonymous):

would it change to just n?

OpenStudy (anonymous):

\[like \sum_{y=1}^{n}\]

hartnn (hartnn):

absolutely correct :) so now you have \[\sum_{1}^{n}y-a\] does it look familiar to any formula i have given??

hartnn (hartnn):

if you are not comfortable with substitution,then i have another approach also...want that?

OpenStudy (anonymous):

Yes please

OpenStudy (anonymous):

\[\sum_{1}^{n}y - an\]

hartnn (hartnn):

ok,lets stick to \[\sum_{a+1}^{a+n}x\] this implies the sum starting from x=a+1 to x=a+n so when substituted,we get a+1+a+2+a+3+a+4+.......a+n got this?

OpenStudy (anonymous):

yes

hartnn (hartnn):

good :) u agree that there will be 'n' times a ---->n*a and the sum from 1 to n.....like 1+2+3+4+....n

OpenStudy (anonymous):

would it be \[\frac{ n(n+1) }{ 2 }-an ?\] for the mean then?

OpenStudy (anonymous):

yes

hartnn (hartnn):

from where did u get the minus??also u forgot to recall about 1/n outside the summation

OpenStudy (anonymous):

\[from \sum_{1}^{n}y-a\]

OpenStudy (anonymous):

if i bring in the 1/n, then i would have (n+1)/2 +/- an?

hartnn (hartnn):

lets follow only one method,(forget about substitution for time being)you got a*n because there were 'n' times a also 1+2+3+4....+n---->n(n+1)/2 so \[\frac{1}{n}(an+\frac{n(n+1)}{2})\] will give you a+(n+1)/2 which is the mean

OpenStudy (anonymous):

oooh.... i see now thanks. I would follow the same method if find variance?

hartnn (hartnn):

i made a mistake in substitution as y=x-a x=y+a so summation would be for y+a and you would get same answer (n+1)/2 +a and not - yes,for variance there is also the formula like mean......do u need it? same steps can be followed,but it would be more difficult because it involved square terms.....

OpenStudy (anonymous):

yes please if it is not too much trouble?

hartnn (hartnn):

sure :) \[\sum_{a+1}^{a+n}(x-MEAN)^{2}f(x)\]

hartnn (hartnn):

oh sorry p(x) not f(x)

OpenStudy (anonymous):

ok so not the usual V(x) = E[X^2] - (E[X])^2 ? because it would be more efficient to find E[X^2]? or is that where it gets complicated?

hartnn (hartnn):

that usual expression is another representation of variance you will calculate E[x^2]as \[\sum_{a+1}^{a+n}x^{2}p(x)\] and then subtract square of mean both expression will give same value although which one will be less complicated will depend on function

OpenStudy (anonymous):

Thanks so much for the help! ^_^ would the variance be (2n+1)(n+1)/6 + 2a^2 + a ?

hartnn (hartnn):

i am not getting that,can u show your work?? also since there is - sign in th formula, 2 'a^2's gets cancelled and does not add up to 2a^2

OpenStudy (anonymous):

ok. i started off with \[\frac{ 1 }{ n }\sum_{1}^{n}(y+a )^2\]

OpenStudy (anonymous):

is that correct so far?

hartnn (hartnn):

yes,correct

hartnn (hartnn):

but for E[x^2] remember to subtract the square of mean from this for variance

OpenStudy (anonymous):

ok, so i just squared it and i have |dw:1345142966030:dw|

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