Parametric and non-Parametric Data

If your data is “normally distributed”, then it can be examined using “parametric” statistics such as mean, variance, standard deviation, etc.

In R:

meandata<- mean(data_set)
variance.data<-var(data_set)
std.data<-(sqrt(var(data_set))) or
std.data<-sd(data_set)

---

Transcript

And so if you have data that are normally distributed (so it follows a Gaussian distribution), then we can say that we can describe it using parametric statistics. Those statistics we've talked about earlier: mean, variance, and standard deviation. And we can calculate those in R by simply saying, "mean of our data frame", "variance of the data frame", and "the standard deviation of something" the square root of the variance or we can say directly calling the function speed on our data frame, and while we have our standard deviation - so it's easy to calculate the parametric statistics.