Ladislaus Bortkiewicz famously looked at the number of Prussian soldiers who had been kicked to death by horses over about 200 years. He found a distribution that looked like this:
In most years (109) no Prussian soldiers were killed by horses. In 65 years, only one soldier died this way, until in one particularly bad year, 4 Prussian soldiers were killed by horses. If you wanted to predict this variable, what would you use?
A) Spearman correlation.
B) Non-linear regression.
C) Poisson regression.
D) Logistic regression.

Question

Ladislaus Bortkiewicz famously looked at the number of Prussian soldiers who had been kicked to death by horses over about 200 years. He found a distribution that looked like this:
 In most years (109) no Prussian soldiers were killed by horses. In 65 years, only one soldier died this way, until in one particularly bad year, 4 Prussian soldiers were killed by horses. If you wanted to predict this variable, what would you use?
A) Spearman correlation. 
B) Non-linear regression. 
C) Poisson regression. 
D) Logistic regression.

Quizplus · Accepted Answer

The distribution of the number of Prussian soldiers killed by horses follows a Poisson distribution, as the data involves counting events (number of soldiers killed by horses) in a specific time period (200 years) with a low probability of occurrence. Poisson regression is the appropriate tool to use for predicting counts in this scenario.

Ladislaus Bortkiewicz Famously Looked at the Number of Prussian Soldiers