In the analysis of Twisty Little Passages, In the "importance sampling 
solution" it is said that we could give a weight of A/B of the sample got 
with "W". But that sample value (degree) is B! So sample * weight gives B * 
A/B = A.

1. Why do we even need that sample as we don't even use its value, why 
should we even query the degree of R2? We don't even need to walk.
2. This just ends up that instead of querying K rooms, we query K/2 of them 
and count each degree twice. How is that even different than computing the 
average degree of K/2 rooms?
If we look at the example given, 8/6 is the exact same result we get if we 
take the average degrees of the rooms we got with the T queries(R1 : 1, R2 
: 1, R3 : 2 => avg 4/3)

Either I misunderstood the explanation  or something is wrong there, as 
implementing that solution gives wrong answer, which is normal as it's the 
same than using the average degree of the samples.

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