39 - The gamma distribution - an introduction

This video provides an introduction to the gamma distribution: describing it mathematically, discussing example situations which can be modelled using a gamma in Bayesian inference, then going on to discuss how its two parameters affect the shape of the distribution intuitively, and finally ending with a derivation of the mean of the distribution.
If you are interested in seeing more of the material, arranged into a playlist, please visit: • Bayesian statistics: a... Unfortunately, Ox Educ is no more. Don't fret however as a whole load of new youtube videos are coming soon, along with a book that accompanies the series: www.amazon.co.... Alternatively, for more information on this video series and Bayesian inference in general, visit: ben-lambert.co... For more information on econometrics and Bayesian statistics, see: ben-lambert.com/

[@brucelam115]

Dude, THIS is the kind of education worth paying for, not whatever my professors are doing

[@diyasharma96]

Superb. Thank you for giving me the intuitive understanding that I needed in just 14 minutes (was watching at 1.25x). The stuff in other places was so dense as to be practically counterproductive; I pored over "recommended" texts for hours before a search online led me to this beauty. Very very grateful for your generosity. Two important points:
[1] At 08:16, I'm pretty sure you meant to say "Y" instead of "lambda". I don't know why nobody's pointed this out for 6 years. If I'm not wrong, perhaps you could add a simple note / annotation at that point on the video so that others don't get thrown by that minor blip in an otherwise superlative effort.
[2] The freehand graphs, especially the one for alpha = 3, didn't seem very reliable. So it gave me a lot of confidence to see the MATLAB projections. Please never stop using those!

[@imrannooraddin1876]

What the fuck is going on

[@mkrcy]

xd

[@alitaha1200]

one must imagine sisyphus happy

[@Robertfrench3364]

Thanks for the video! The textbook I have been using covers the expected value for gamma far too quickly. You really laid it out and made it easy to comprehend!

[@nickhead2481]

Brilliant explanations - thanks a lot! Can you take over from my uni lecturers please?

[@observever7808]

AWESOME, no crap, straight to what we need to know!

[@nasgaroth1]

Man, this guy explain nothing, simply theoretical crap. Where is an example, some information from practice ? Nothing simply theoretical shit

[@brockobama257]

No way I clicked on this video expecting shitty audio but you sound fantastic. Very rare very rare…

[@katyadimitrovapetrova9343]

omg I was struggling with this gamma distribution for a week now. thanks!

[@atewary3101]

Im confused.
When changing values of alpha, you say anything not a function of y cancels out- you take the Beta^alpha part out.
When changing values of Beta, you keep the Beta^alpha bit in? This still is not a function of y.

[@anthonyfernandezgonzalez8262]

Thank you so much, great lesson!

[@dARKf3n1Xx]

gotta like this, so new updated explanation can come :P

[@lazy_hiker_guy]

If this is Ben Lambert, then why didn't you post this video on your page as well? Would have been easier for us since it would reduce the search time. Btw your videos are a life saver.

[@Coughi3]

thank you very much, great video and explanation

[@jacobherz9454]

love the way he says beeta

[@yassine20909]

Excellent explanation, thank you

[@dursundurmaz915]

Really helpfull, clear english, great expression

[@mo8144]

Brilliant explanation !!!

[@TheDantsu]

Best explanation ever. Thank you.

[@samad.chouihat4222]

could you please tell me the name of the software he used to draw those functions

[@TheXxsayaoxx]

MATLAB?

[@internetroamer8063]

it is MATLAB

[@basilkjeemon196]

brilliant explanation

[@AronBattistella]

That was a great explanation. Thank you!

[@fo89jsafglpwo]

Hey its good explanation, thanks budd, I can now understand what the actual fuck is going on.
But there's one question, shouldn't the Beta be replaced in the p.d.f. by 1/Beta? Since when the parameter Beta increases, the change in specific p.d.f. should be exactly the opposite of your graph.
**update
Sorry I was wrong. It's just different presentation of the parameter. Thanks!

[@malintha]

Here beta represents the rate of change. I think in the other way beta representation the time for the next event to occur.

[@baselosama781]

can you share the matlab code with me please

[@abhayanand1668]

Thank you

[@oxeduc4209]

Hi, thanks for your kind words. Glad you found it helpful! Best, Ben

[@MsKisshello]

thank you!

[@klam77]

Brilliant.

[@timhale2704]

Fantastic and very clearly explained! Thank you :)

[@achillesarmstrong9639]

very nice video. bravo

[@janezhu2091]

such a beautiful explanation!

[@fredbig6789]

You saved my ass.

[@biniljoy2542]

Can you please start from the base, I didn't understand anything.

[@PragyadityaDas94]

Really very helpful

[@achillesarmstrong9639]

good video

[@DanyangZhang]

Nice explanation!

[@lukepaluso9863]

you're awesome

[@kadiusvain1102]

Either I’m dumb as fuck or I’m just not paying attention like WTF if I wanted school I’ll go back for that lol more simple please

[@aryamandwivedi1277]

Sorry for waiting for 10 years
But your notation for gamma distribution is wrong because you interpreted the order of parameters incorrectly😊

[@groovyagain96]

very helpful. Thank you

[@shhim8229]

very helpful

[@aseefzahir8789]

Brilliant~ you

[@KOBILLIN]

assist me in this question
let x be a bin(2,p) and y be a bin(4,p). if the pr(X>1)=5/9. find pr(Y.1)

[@bobbynazaris750]

Thank you