1. Your first ggplot2 figure
    The grammar of graphics in the Code editor's R mode — data, aesthetics, geometries — built into a scatter plot with a fitted trend.
  2. Groups, facets, and themes
    Compare conditions in one figure — colour-mapped groups, small-multiple facets, and a theme that reads well in print.
  3. Distributions and histograms
    Histograms, density curves, and honest binning — showing the shape of your data before you summarise it away.
  4. Summaries and error bars
    Aggregate raw observations to mean ± error in base R, then plot bars, error bars, and the raw points over them.
  5. Fitting and plotting models
    Fit with lm(), read the coefficients you'll quote, and draw the model over the data with a confidence ribbon you computed yourself.