The data is very highly skewed, as the mean and median and extraordinarily far apart. In cases where the data is skewed, it is best to use the Median and the IQR to negate outliers.
Yes, it seems seeding clouds is very effective. We can see this becuase the median rainfall for unseeded clouses is very small at 44.2 acre-feet compared to the median rainfall for seeded clouds at 221.6 acre-feet. Thats a huge increase in rainfall!
It’s difficult to assess this histogram becuase almost all the data points are clustered into one single fraction of the graph, making it very difficult to discern the majoirty of the values. The spread clearly skews right, but its hard to tell by how much since most of that data is indeterminable from this histogram/
I would reccomend taking a log of the data. This would allow us to clearly see the data in a more symetrical, discernable fashion.
rain<-c(2745,1697,1656,978,703,489,430,334,302,274,274,255,242,200,198,129,119,118,115,92,40,32,31,17,7,4)
hist(rain, main ="Seeded clouds rainfall", col = "blue", xlab = "Rainfall in acre-feet", breaks = 30)
rain<-c(2745,1697,1656,978,703,489,430,334,302,274,274,255,242,200,198,129,119,118,115,92,40,32,31,17,7,4)
lograin<-log(rain, base=10)
hist(lograin, main ="Seeded clouds rainfall", col = "lightblue", xlab = "Log rainfall in acre-feet", breaks = 20)