# normal.params: Calculate the Normal Mean and Standard Deviation Using the... In mdenwood/bayescount: Statistical Analyses and Power Calculations for Count Data and Faecal Egg Count Reduction Tests (FECRT)

## Description

Function to calculate the equivalent values for the mean and standard deviation of a normal distribution from the mean and standard deviation of the log-normal distribution. Outputs from this function can be used with the dnorm() function, and with the normal distribution in JAGS.

## Usage

 `1` ```normal.params(log.mean, log.sd, coeff.variation=sqrt(exp(log.sd^2)-1)) ```

## Arguments

 `log.mean` either a single value or vector of values for the mean of the lognormal distribution. `log.sd` either a single value or vector of values for the standard deviation of the lognormal distribution. Ignored if values are supplied for coeff.variation. `coeff.variation` either a single value or vector of values for the coefficient of dispersion.

## Value

A list with elements representing the mean of the normal distribution, the standard deviation of the normal distribution, and the coefficient of variation.

`lnormal.params`
 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## Not run: lmean <- 2.5 lsd <- 0.2 mean <- normal.params(lmean,lsd)[[1]] sd <- normal.params(lmean,lsd)[[2]] curve(dlnorm(x, lmean, lsd), from=0, to=25) dev.new() curve(dnorm(x, mean, sd), from=0, to=25) ## End(Not run) ```