Using Poisson Approximation to Compare Infection Rates in Village A and B

In summary, there are 60 infections in village A per month and 48 infections in village B per month. Method 1 (Working method) does not work, while Method 2 (Through linear combination of poisson (?Cannot get it to work?)) yields a probability of 2.66x10-4 that the no of infections in B exceeds no of infections in A.
  • #1
qazxsw11111
95
0
There are 60 infections in village A per month and 48 infections in village B per month.
Let A be no of infections in village A per month and B be no of infections in village B per month. Assume occurrence is independent and random.

So
Method 1 (Working method):

A~Po (60) and B~Po (48)

Using a suitable approximation, find the probability that in 1 month, the no of infections in B exceeds no of infections in A.

Since λ>10, A~ N(60,60) and B~N(48,48) approximately

B-A~(-12, 108)

P(B>A)=P(B-A>0)=0.115

This I can understand but when I tried another method, it didnt work.

Method 2: Through linear combination of poisson (?Cannot get it to work?)


A-B ~ Po(12)

Since λ>10, A-B~N(12,12)

P(A<B)=P(A-B<0)=2.66x10-4

Why the difference? Why does the second method not work?
 
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  • #2
qazxsw11111 said:
A-B ~ Po(12)

Could you explain the reasoning for this step please?
 
  • #3
I thought Poisson can perform linear combinations. I know A+B~Po(60+48) but A-B? I assumed minus is possible.
 
  • #4
qazxsw11111 said:
I know A+B~Po(60+48) but A-B?

Ok. If A-B were Poisson, what would be the frequency, mean and variance values?
 
  • #5
λ1+λ2 in poisson formula is e^-(λ1+λ2)=e^-λ1*e^-λ2. but if you use λ1-λ2 we have e^-(λ1-λ2)=e^-λ1*e^λ2=e^λ2/e^λ1
 
  • #6
qazxsw11111 said:
I thought Poisson can perform linear combinations.

Linear combinations of Poisson random variables are actually Compound Poisson - not pure Poisson but an interesting topic in their own right.

qazxsw11111 said:
P(A-B<0)=2.66x10-4

On second thought, if A-B were Poisson then A-B can _never_ be negative, i.e. the probability would be exactly zero - but since A and B are independent Poisson there's always some chance. If you have access to math or stats software then it would be useful to run some random simulations to check which answer is correct.

Have fun!
 

Related to Using Poisson Approximation to Compare Infection Rates in Village A and B

1. What is Poisson Approximation?

Poisson Approximation is a statistical method used to estimate the probability of rare events occurring in a large sample size. It is based on the Poisson distribution and is often used when the sample size is too large for traditional methods to be feasible.

2. How is Poisson Approximation calculated?

The calculation of Poisson Approximation involves determining the mean and variance of the data, and then using those values to calculate the probability of the rare event occurring using the Poisson distribution formula. This calculation can be done by hand or using statistical software.

3. When is Poisson Approximation used?

Poisson Approximation is used when the sample size is large and the probability of the rare event occurring is small. It is often used in fields such as epidemiology, genetics, and finance to estimate the likelihood of rare events.

4. What are the assumptions of Poisson Approximation?

The assumptions of Poisson Approximation include that the events are independent of each other, the probability of the event occurring is constant, and the sample size is large. Additionally, the events must be rare, meaning that they occur with a low frequency.

5. What are the limitations of Poisson Approximation?

One limitation of Poisson Approximation is that it can only be used for rare events; if the event occurs frequently, the approximation may not be accurate. Additionally, the accuracy of the approximation depends on the sample size and the assumptions made. It is important to check the validity of the assumptions before using Poisson Approximation.

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