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When to use Binomial Distribution vs. Poisson Distribution? For Poisson, bike might get fixed and break yet again in the same day (as said by @JMoravitz) Still, if the chosen time interval (day is an arbitrary choice) is narrowed down to so small that likelihood of breaking twice becomes negligible, Binomial is the model for the distribution
Relationship between poisson and exponential distribution The waiting times for poisson distribution is an exponential distribution with parameter lambda But I don't understand it Poisson models the number of arrivals per unit of time for example How i
Why is Poisson regression used for count data? Poisson distributed data is intrinsically integer-valued, which makes sense for count data Ordinary Least Squares (OLS, which you call "linear regression") assumes that true values are normally distributed around the expected value and can take any real value, positive or negative, integer or fractional, whatever Finally, logistic regression only works for data that is 0-1-valued (TRUE-FALSE
When to use an offset in a Poisson regression? [duplicate] Here is an example of application Poisson regression is typically used to model count data But, sometimes, it is more relevant to model rates instead of counts This is relevant when, e g , individuals are not followed the same amount of time For example, six cases over 1 year should not amount to the same as six cases over 10 years So, instead of having
How to interpret coefficients in a Poisson regression? This was in discussions of interpreting logistic regression coefficients, but Poisson regression is similar if you use an offset of time at risk to get rates You add first all the coefficients (including the intercept term) times eachcovariate values and then exponentiate the resulting sum