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Conquering Data Analysis in R
Introduction
Welcome! Watch this introduction first :) (1:12)
The Package: Notebooks, data, and practice exercises for all lessons
Setting up your environment (6:11)
Lesson 1: Working with data
Using an R notebook (4:49)
Importing data (10:12)
Inspecting data (9:54)
Transforming data (8:46)
Subsetting data (9:48)
Lesson 2: Plotting bar charts
Plotting counts of a factor (8:46)
Plotting numeric variables (6:46)
Adding labels to the bars (7:24)
Advanced notes on aes() (6:02)
BONUS: Saving images of your plots
Lesson 3: Plotting scatter plots
Including colors, sizes, shapes, and transparency (7:22)
Lesson 4: Boxplots, histograms, densities, and violin plots
Plotting the distribution of a numeric variable (6:42)
A note on bin width (4:51)
Overlaying plots (6:23)
Lesson 5: Plotting line and area charts
Line charts (5:46)
Area charts (6:44)
Lesson 6: Styling plots
Reordering the legend (4:54)
Changing and tweaking ggplot themes (9:06)
Using the ggplot theme documentation (5:25)
Theme showcases: the good and the ugly (4:28)
Fun with color schemes (6:08)
Advanced color strategies (7:02)
Lesson 7: Plotting a heatmap
Creating a heatmap from a matrix (6:58)
Various transformations and tweaks for a heatmap (11:53)
BONUS: How to get a matrix of count data
Lesson 8: Statistics
Creating a simulated dataset (5:25)
Correlation and linear regression (7:02)
t-tests (5:47)
Advanced notes on multiple hypothesis testing and p-value distributions (9:32)
Lesson 9: Data wrangling
Filtering data (4:42)
Renaming factor levels (2:37)
Dealing with missing data (8:14)
Lesson 10: PCA
Principal component analysis (21:46)
Changing and tweaking ggplot themes
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