☕ Poisson Distribution through Bananas, Sweets, Stars, Heart Beats and Cigarettes
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Uploaded by chris12dec on Aug 31, 2011
This is Upper Sixth Statistics. If you haven't studied it before, I'm sorry, but you'll get lost around the point when I'm writing on the banana. For you I tried to be as weird as possible to still keep you interested!
The point of the video is to go into more detail than you get in textbooks on,
✵ the interpretation of the three conditions in different contexts,
✵ how meeting all three conditions is sufficient for a Poisson distribution model and
✵ that calculated chances are at best close approximations of true chances.
There's no point me coming on here and doing a Khan Academy/Exam Solutions/Patrick JMT and just rehashing what you can see in your Heinemann book, which is why I barely went into calculations.
A couple of further notes,
1. The mean of experimental data being roughly equal to the variance is not sufficient for a Poisson distribution model (it is only necessary). This means that such calculations are useful only for ruling out a situation from following a Poisson distribution, e.g. for heart beats per minute, the mean could be about 72, but the variance only about 4, which would show once again that heart beats per minute don't follow a Poisson Distribution.
2. Yes: Number of finishers in the Goldbears fun run during a 5-minute period also isn't at a constant average rate.
3. The origin of the Poisson probability function, and the three conditions, is the Binomial distribution. There are some videos on this knocking about already.
4. I haven't really explained what the Poisson distribution is in this video. The Poisson distribution is a table of all possible outcomes, i.e. 0, 1, 2, 3, 4, 5, ... together with the probability of each outcome occurring. The shorthand notation for this infinitely long table is ~Po(λ).
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nice explanation
sonicsizzors 2 months ago
Excellent video!
hayleshobthegreat 4 months ago
you are so jokes XD
tsasnm 4 months ago