qq plot in R to check normality of the distribution?

Question

I have been reading a tutorial from https://www.datanovia.com/en/lessons/anova-in-r/ on how to perform ANOVA test in R. However, my question is regarding checking normality of the distribution in general.

There is an option to do a QQ plot with the ggqqplot function. However I do not know how to define the function. From what I can see in the tutorial on the datanovia, they use residuals from the linear model:

# Build the linear model
model  <- lm(weight ~ group, data = PlantGrowth)
# Create a QQ plot of residuals
ggqqplot(residuals(model)

Then I performed the same test this way:

ggqqplot(PlantGrowth, "weight")

I expected to see the same result; however, the results differ.

From the documentation of the function ggqqplot it is not clear to me how is it correct to define it. Does someone have an explanation?

Thanks:D

Answer 1

You would just do ggqqplot(PlantGrowth) as long as that variable is a vector of numeric values. the function only takes a vector of numeric values and gives you something like this ex: ggqqplot(iris$Sepal.Length)