The statistics of falling objects.

Now it turns out to be a cumulative log normal distribution (in which a log normal distribution is simply integrated). 

 

Once you know this you can try to fit it with the parameters of this type of curve and calculate back for any amount of coins or any thickness of the "coinrod"what its chance will be to land on its edge. 

 

It turns out to be that the estimated chance based on these limited amount of numbers of coin-rod-flips  the chance of a 5 Eurocent landing on its edge is about 1 in 300-400. For more accuracy it would be better to increase the number of coin-rod-flips. of course, But for now it will do. 

 

You may think that we can stop here right now, but then you are mistaking, There is more. This subject turned out to be far more interesting then expected and therefor I continue. 

 

You see there are questions that rose based on this issue. since we could ask

a) what would be the results if we replace the coin rod for an other rod like objects, Like a tube and does the weight of these objects influence it.  

b) can we alter the shape of the rods by cutting off some part in such a way that we obtain a non right angled rod due to which the coin side is increased

c) What would be the results be if the rod would be modified in all kinds of ways. and weight distributions within the rod. 

 

and of course these results would bring about some more questions, So this was an interesting start of an interesting subject: in general Falling objects, How would they behave statistically. Not very high tech I agree but intersting non the less. 

 

This "reseach" is still in progress, but is shifted aside from time to time for even more research. 

 

some more (recent) data to be added:

 

no coins      1     2      3     4      5    6    7     8      9     10 

head           52   52    51   94    87   x   60   50    x     28

coin            48   48    57  98    94   x   64    41    x     24

edge          0      0      2     8     19    x   76   109  x    148