I have expenditure data in several regions, and for each of them i know mean expenditure, standard deviation and skewness in original scale. Since data are skewed i want to compute probability of being below certain expenditure level (for example 1500
$) with log normal distribution. For example in one region i have mean expenditure m=2000
$, sd=1000, and skweness=1.1. in that case can i use
or i need to transform evertything in log scale first? In plnorm parameters are described "mean and standard deviation of the distribution on the log scale with default values of 0 and 1 respectively." If i need to transform it first, is the following correct:
m=2000 s=1000 lsm=log(m)-(1/2)*log((s/m)^2+1) lssd=sqrt(log((s/m)^2+1)) plnorm(log(1500),lsm,lssd)
I guess this is very related to post How to calculate log-normal parameters using the mean and std of the given distribution but in my case i also need to be sure i am using plnorm/pnorm correctly.