MHB Using gamma function to solve an integral

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The discussion centers on solving the integral of the form $$\int^\infty_0 e^{-\frac{2x}{\theta}}x \,dx$$ using the gamma function. The user is confused about how to manipulate the exponent and constants to transform the integral into a gamma function format. They question the removal of the factor (2/theta) from the exponent and its subsequent division in the final steps. A substitution is suggested, letting t = (2x/theta), which simplifies the integral and allows the application of the gamma function definition. The conversation highlights the importance of proper substitution and understanding the gamma function's properties in integral transformations.
mathjam0990
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Hello,

I have attached a picture of the integral I am solving. I understand at the end how they turned the function (in the second to last step) into gamma(2) BUT what I do not understand is how you can simply just remove the (2/theta) out of the exponent of e, turn it into gamma(2) then divide it by (2/theta)^2 in that last step. Based on the fact that gamma(a) = integral of [ya-1 * e-y]dy I see for this particular example in question that the (2/theta) is out of place (so to say) if we are trying to get our integral to take the form of the integral equaling gamma(a). So, with all that being said, how can we simply just take that (2/theta) out of the exponent of e, turn the whole thing into a gamma and then just divide by (2/theta)^2 ?? Is there a trick or something I am overlooking? Please help me if you can!

Thank you!
 

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Let us solve

$$\int^\infty_0 e^{-\frac{2x}{\theta}}x \,dx $$

Let $t = \frac{2x}{\theta}$ which implies that $dx = \frac{\theta}{2}dt$

$$\int^\infty_0 e^{-t}\times \frac{\theta}{2}t \times \frac{\theta}{2} \,dt = \frac{\theta^2}{4}\int^\infty_0t e^{-t}\,dt$$

Then use the definition of the gamma function
 
Thank you ZaidAlyafey!
 
Greetings, I am studying probability theory [non-measure theory] from a textbook. I stumbled to the topic stating that Cauchy Distribution has no moments. It was not proved, and I tried working it via direct calculation of the improper integral of E[X^n] for the case n=1. Anyhow, I wanted to generalize this without success. I stumbled upon this thread here: https://www.physicsforums.com/threads/how-to-prove-the-cauchy-distribution-has-no-moments.992416/ I really enjoyed the proof...

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