Convert a binomial distribution to a normal (gaussian) distribution with specified mu and sd
Arguments
- x
the binomially distributed vector
- mu
the mean of the normal distribution to return
- sd
the SD of the normal distribution to return
- size
number of trials (set to max value of x if not specified)
- prob
the probability of success on each trial (set to mean probability if not specified)
Examples
x <- rbinom(10000, 20, 0.75)
y <- binom2norm(x, 0, 1, 20, 0.75)
g <- ggplot2::ggplot() + ggplot2::geom_point(ggplot2::aes(x, y))
ggExtra::ggMarginal(g, type = "histogram")