How do I change a poisson spreadsheet into a bivariate version?

In summary, the conversation discusses using a bivariate Poisson distribution in an excel spreadsheet to calculate the probability of correct scores in soccer matches. The suggested method is to multiply the Poisson distributions of each variable if they are independent, but if they are not independent, information about the correlation is needed. There is also a mention of an additional restriction involving draw probability as a parameter for distribution. The speaker has tried to calculate Pdraw using this method, but it does not correlate with the actual data, suggesting that some factors, such as draw probability, need to be taken into account for a more accurate Poisson distribution. The question then becomes how to incorporate draw probability into the calculation.
  • #1
pswirly
1
0
I have an excel spreadsheet that uses poisson to figure out the probability of correct scores in soccer matches.

How do I amend the spreadsheet to use a bivariate poisson distribution?
 
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  • #2
If the two variables are independent, just multiply the Poisson distributions of each. If they are not independent, what information about the correlation do you have?
 
  • #3
HallsofIvy said:
If the two variables are independent, just multiply the Poisson distributions of each. If they are not independent, what information about the correlation do you have?

1. There is additional restriction - draw probability as parameter for distribution. Draw - this is the case when M(t) = N(t).
In common Pdraw = sum(M(ti)*N(ti)), i = 0, 1, 2 ...

2. I have tried to multiply the Poisson distributions of each for calculation the spreadsheet, but calculated Pdraw is lower than fact Pdraw. And calculated data don't correlate with fact data. Results from this that I don't take into account some factors (first of all, draw probability), which shall correct Poisson distribution.

How I can take into account draw probability to modificate the Poisson distribution?
 

Related to How do I change a poisson spreadsheet into a bivariate version?

1. What is a Poisson spreadsheet and how is it different from a bivariate version?

A Poisson spreadsheet is a type of data set that displays the frequency or number of occurrences of an event within a given time or space. A bivariate version, on the other hand, includes two variables that are being analyzed together, allowing for a more detailed and nuanced view of the data.

2. Why would I need to change a Poisson spreadsheet into a bivariate version?

A Poisson spreadsheet may only provide limited information about the relationship between two variables. By converting it into a bivariate version, you can gain a better understanding of how these variables are related and potentially identify patterns or trends that may not have been apparent before.

3. How do I convert a Poisson spreadsheet into a bivariate version?

To convert a Poisson spreadsheet into a bivariate version, you will need to add a second variable to your data set. This can be done by creating a new column or row and inputting the relevant data. You may also need to use a statistical software or program to analyze the data and create a bivariate graph or chart.

4. What types of data are suitable for a bivariate analysis?

Any type of data that involves two variables can be suitable for a bivariate analysis. This could include variables such as age and income, education level and job satisfaction, or temperature and precipitation. The key is to have two distinct variables that can be compared and analyzed together.

5. Are there any limitations to using a bivariate version of a Poisson spreadsheet?

While a bivariate version may provide more detailed information than a Poisson spreadsheet, it is important to note that it may not be suitable for all types of data. Bivariate analysis assumes a linear relationship between the two variables, so if the data follows a different pattern, the results may be misleading. It is always important to carefully consider the data and its characteristics before conducting a bivariate analysis.

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