Find Expected Number of Cakes per Person: Bernoulli to Gamma

AI Thread Summary
To find the expected number of cakes per person when distributing w cakes among n people, the discussion explores various probability distributions, including Bernoulli, Binomial, Poisson, Uniform, Exponential, Normal, Chi-square, and Gamma. Participants emphasize that the distribution in question is discrete. There is a request for input on what methods have been attempted to solve the problem, indicating a collaborative approach to understanding the statistical concepts involved. The conversation highlights the need for a foundational grasp of probability and statistics to tackle the problem effectively. Engaging with the problem through discussion is encouraged for better comprehension.
ackr1201
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Solve this??

There are w cakes and n people. The cakes are distributed to people randomly. Find the expected number of cakes a 'i' person can receive. The distribution is:
a) Bernoulli distribution

b) Binomial distribution

c) Poisson distribution

d) Uniform distribution

e) Exponential distribution

f) Normal distribution

g) Chi-square distribution

h) Gamma distribution
 
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what did you try??
Is the distribution discrete or continuous??
 


@micro mass : I didn't get.. I am poor at propbabilty and statistics

It follows discrete distribution

Plz help me..
 


I am helping you, but I'm not just telling the answer until you tell me what you think and what you tried.
 
I was reading a Bachelor thesis on Peano Arithmetic (PA). PA has the following axioms (not including the induction schema): $$\begin{align} & (A1) ~~~~ \forall x \neg (x + 1 = 0) \nonumber \\ & (A2) ~~~~ \forall xy (x + 1 =y + 1 \to x = y) \nonumber \\ & (A3) ~~~~ \forall x (x + 0 = x) \nonumber \\ & (A4) ~~~~ \forall xy (x + (y +1) = (x + y ) + 1) \nonumber \\ & (A5) ~~~~ \forall x (x \cdot 0 = 0) \nonumber \\ & (A6) ~~~~ \forall xy (x \cdot (y + 1) = (x \cdot y) + x) \nonumber...
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