- Pleleminary tasks
- Example data
- Create QQ plots
- Related articles
- See also
- Infos
Previously, we described the essentials of R programming and provided quick start guides for importing data into R.
Here, we’ll describe how to create quantile-quantile plots in R. QQ plot (or quantile-quantile plot) draws the correlation between a given sample and the normal distribution. A 45-degree reference line is also plotted. QQ plots are used to visually check the normality of the data.
Launch RStudio as described here: Running RStudio and setting up your working directory
Prepare your data as described here: Best practices for preparing your data and save it in an external .txt tab or .csv files
Import your data into R as described here: Fast reading of data from txt|csv files into R: readr package.
Here, we’ll use the built-in R data set named ToothGrowth.
# Store the data in the variable my_datamy_data <- ToothGrowthThe R base functions qqnorm() and qqplot() can be used to produce quantile-quantile plots:
- qqnorm(): produces a normal QQ plot of the variable
- qqline(): adds a reference line
qqnorm(my_data$len, pch = 1, frame = FALSE)qqline(my_data$len, col = "steelblue", lwd = 2)
It’s also possible to use the function qqPlot() [in car package]:
library("car")qqPlot(my_data$len)
As all the points fall approximately along this reference line, we can assume normality.
- Creating and Saving Graphs in R
- Scatter Plots
- Scatter Plot Matrices
- Box Plots
- Strip Charts: 1-D scatter Plots
- Bar Plots
- Line Plots
- Pie Charts
- Dot Charts
- Plot Group Means and Confidence Intervals
- Graphical Parameters
- Lattice Graphs
- ggplot2 Graphs
This analysis has been performed using R statistical software (ver. 3.2.4).
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