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In this course, you will learn:
- How to use histograms and box plots to graphically illustrate the spread of a variable using real-world data on British monarchs, Australian salaries, Panamanian wildlife, and US cigarette usage.
- Understand key data visualization principles such as correlation, linear relationships, and log scales as well as how to evaluate data plots.
- How to use scatter plots and line plots to investigate the relationship between two continuous variables.
- Explore data on life expectancy, use of technology, COVID-19 coronavirus cases, and Swiss juvenile criminals.
- Introduced to two other common visualizations, bar plots and dot plots, which are frequently used to investigate the relationship between categorical and continuous variables.
- Explore famous athletes, health survey data, and the global price of a Big Mac.
- Learn how to use color and form to make your data visualizations clearer and easier to understand, especially when working with more than two variables at once.
- Explore Los Angeles property prices, technology stock prices, math anxiety, the best hiphop tunes, scotch whisky tastes, and olive oil fatty acids.
- How to recognize and prevent the most frequent story issues. For example, how can you avoid making plots that are misleading or difficult to decipher, and will your audience grasp what you're trying to tell them? Everything will be revealed!
- About wind directions, asthma prevalence, and German Federal Council seats.
Syllabus:
- Visualizing distributions
- Visualizing two variables
- The color and the shape
- 99 problems but a plot ain't one of them
