Lesson 16: Visualizing Data II - Errorbars and RibbonsLesson 16: Visualizing Data II - Errorbars and Ribbons
In this chapter we'll continue working on scatterplots, but we'll focus on several enhancements and manipulations that may be useful. Note that these are not specific to scatterplots, but we will demonstrate them in the context of scatterplots.
- Add errorbars to plots
- Draw arbitrary polygons on charts
- Use the function polygon() to show error ribbons
- Use errorbars or ellipses to show error in two dimensions
- Reverse axes on a plot
The R code file and data files for this lesson can be found on the Essential R - Notes on learning R page.
16.1 - Errorbars - Introducing arrows()16.1 - Errorbars - Introducing arrows()
arrows() can be used to draw arrows from one point to another, but by manipulating the arrow ends it can also create errorbars.
16.2 - Custom Axis Formatting16.2 - Custom Axis Formatting
On occasion we may want to format an axis in units that are different from the units in the variable - in this example the units are days of the year (ordinal days), bu we want to label them with "Month Day" (e.g. "March 10"). Here we'll explore how
axis() can be used to do this.
16.3 - Plotting Errorbars and Preparing to Add Lines16.3 - Plotting Errorbars and Preparing to Add Lines
Here we're putting toghether what we've learned so far in this chapter by adding errorbars for groups of data points to our plot with custom axes. We'll also prepare to add the regression lines, but using
lines() rather than
abline() so as to confine our lines to the range of the predictor variable.
16.4 - Adding Lines and a Small Table to a Plot16.4 - Adding Lines and a Small Table to a Plot
Here we'll conclude this example by adding our lines and a small table that shows the p-values from an ANCOVA on the plot.
16.5 - Plotting Confidence Intervals - Preparing the Data16.5 - Plotting Confidence Intervals - Preparing the Data
In the next example we'll use the function
polygon() to show the 95% confidence interval around the means of some values (Since we're not fitting a model here, so we can't use
predict() as we did previously). Here we'll examine the data an plan the plot.
16.6 - Introducing polygon() and Prepping Data for Ribbons16.6 - Introducing polygon() and Prepping Data for Ribbons
Now we'll introduce
polygon() , show how to use it to create a ribbon, and set up the vectors that we'll need for drawing our 95% CI ribbons.
16.7 - Polygons with Semi-Transparent Colors16.7 - Polygons with Semi-Transparent Colors
Now we'll put all the pieces together to create a plot that shows both the means and 95% CI for the means for soil pH at different distances from the road in the two road treatments.
16.8 - Errorbars in 2 Dimensions & Ellipses16.8 - Errorbars in 2 Dimensions & Ellipses
In this video we'll consider the use to 2-dimension error bars or ellipses to show error in 2 variables.
16.9 - Reversing Axes16.9 - Reversing Axes
We'll return to our earlier discussion of custom axes and consider how we could set up a reversed axis plot.