# Best analysis for count data as response variable

I want to know what is the best way to analyze a data set where my response variable is count data and my explanatory variables are continuous variables. All my variables are not normally distributed. Are GLMs a good option?

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They are. You may want to look at Poisson regression (in R: glm(..., family=poisson, ...)) or, if you have overdispersion, Negbin regression or, if you have "too many" zeros, ZIP regression (Zero-Inflated Poisson).