Is there any link between gamma distribution and normal distribution? Please, help
ok , im not expert but in my opinion i think they are different things , not derived from each other although both are used to convert sample to universe .
Thanks friend, I review for final, just want to make the life easier. :)
good luck all the best :)
:)
WWWWWWWWWWWHHHHHHHHHAAAt?? I don't want to study anymore. I go to sell Hoagies. :)
lol
\[f(x)= \frac{1}{2\sqrt{2\pi}}e^{(-1/8)x^2}\] \[F(x)=\int_{-\infty}^{x} f(t)dt=\int_{-\infty}^{x}\frac{1}{2\sqrt{2\pi}}e^{(-1/8)t^2}dt\] \(W = X^2\) \[G(W)= F(\sqrt w)- F(-\sqrt w)\] \[G'(W)= F'(\sqrt w)- F'(-\sqrt w)\] the last line is \[G'(W) = g(w) = f(\sqrt w) ((1/2)w^{-1/2} - f(-\sqrt w)((1/2)((-1/2)w^{-1/2}\] I don't get the last line, please, explain me
I type the last line wrong, it is
\[G'(W) = g(w) = f(\sqrt w) ((1/2)w^{-1/2}) - f(-\sqrt w)((-1/2)w^{-1/2})\]
I have group study now, appreciate any tips. Please, leave your guide here. I'll be back right after class. :)
the last line is derived from using chain rule \[f(x) = F'(x)\] \[(\pm \sqrt{w})' = \pm (1/2)w^{-1/2}\] regarding your question on distributions the gamma distribution can resemble the normal distribution as k-> infinity "For large k the gamma distribution converges to Gaussian distribution with mean μ = kθ and variance σ2 = kθ2." http://en.wikipedia.org/wiki/Gamma_distribution#Others
Thank you. :)
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