For part c, what is the difference between 'expected value' and 'most probable value' and why aren't they the same thing?

I initially thought it would just be the peak of the graph so I just plotted it on desmos and used the peak x-value but that didnt seem to work?

Any help always appreciated.
Original post by mosaurlodon
For part c, what is the difference between 'expected value' and 'most probable value' and why aren't they the same thing?
I initially thought it would just be the peak of the graph so I just plotted it on desmos and used the peak x-value but that didnt seem to work?
Any help always appreciated.

Theyre the usual definitions, though b) is for rays arriving and c) is for rays detected which are different random variables due to the saturation. The expected value is a standard a level concept and for a discrete random variable is the sum over n of
x_n p(x_n)

The most probable (mode, integer) and the expected value (mean, real) for a standard poisson are related though
https://en.wikipedia.org/wiki/Poisson_distribution
You can work it out without calculating the actual probabilities (hint 3, b).

The famous example of the mode and mean being different is that the mean number of legs a person has is something like 1.995 as noone has more than 2 but a few people have 0 or 1. The mode is obviously 2.
(edited 2 months ago)
Oh so the expected value is just the value for lambda?

(edited 2 months ago)
Original post by mosaurlodon
Oh so the expected value is just the value for lambda?

For a standard poisson distribution the mean or expected value is lambda. However, for c) its a slighlty modified poisson distribution due to the saturation and the mean will be a bit less than lambda.
Wait actually im a little confused about the standard expected value part - using desmos I just did P(x_n)*x_n and summed it but this seems to approach 0 rather than lambda.

I also dont really get how the saturation part works - I know intuitively it shifts the entire graph to the left, since the lower values must be more probable but dont really know by what factor it shifts?
90*0.03777 = 3.4
When you calculcate the expected value, you dont divide by "t", its the random value multiplied by the probabilitiy (summed).

For the saturation, the new p(5) will be the old P(X>=5) for the poisson as all values of 5 or greater are mapped to 5. Thats why part a) gets you to calculate the probability of saturation.
Oh I see...
so the value would be 2.530+[part a answer]*5

Thank you very much
Original post by mosaurlodon
Oh I see...
so the value would be 2.530+[part a answer]*5

Thank you very much

Yes, didnt read the first line properly at first.