If the shape is more or less bell shaped, it sounds like you’re dealing with a gaussian distribution. To find the parameters of your gaussian distribution N(mu,sigma^2), take the mean of all your points,that’s mu.. now subtract mu from all the points and take the square of that, finally divide by the number of points, thats your sigma^2.
For example, if you have points 3,4,5 , mu=4 and sigma^2 = (minus1^2+0^2+1^2)/3 = ⅔. This means your points were generated by the normal distribution N(4,⅔) , or in other words drawn randomly from a PDF described by the following function f(x)=1/sqrt(2*pi*sigma^2)*e^-(x-mu)^2/(2*sigma^2).
If you’re not sure that you are dealing with a gaussian distribution, you may have to hypothesise what the distribution may be, or choose a general distribution/model such as a GMM and use EM to fit it to your data.
Here are some links that may be helpful:
http://en.wikipedia.org/wiki/Normal_distribution
http://en.wikipedia.org/wiki/Variance
http://en.wikipedia.org/wiki/Estimation
http://en.wikipedia.org/wiki/Mixture_model
http://en.wikipedia.org/wiki/Expectation_maximization
Feel free to give more details of your problem and maybe i could give a more precise answer.