Module 2: Good Food Gone Bad!

Overview

A wave of food poisoning spreads through the Antarctic base, and the team needs to figure out why. Students investigate a potential food contamination event using descriptive statistics and data visualization to track down the culprit. Along the way, they are introduced to histograms, scatter plots, and box plots in both base R and ggplot2, and they develop an eye for what makes a visualization effective or misleading. By the end of the module, students have solved the problem and begun exploring a dataset of their own for the course’s final project.

Learning Objectives

By the end of this module, students will be able to:

  • distinguish between descriptive and inferential statistics and explain when each is appropriate
  • calculate and interpret measures of central tendency and variation, including mean, median, and standard deviation
  • create histograms and scatter plots using base R syntax
  • build plots iteratively in ggplot2 using ggplot(), aes(), geom functions, labs(), and theme() functions
  • select an appropriate plot type based on the number and types of variables being visualized
  • create histograms, multiple histograms, scatter plots, and box-and-whisker plots in ggplot2
  • evaluate the effectiveness of a data visualization and identify common pitfalls
  • write a research question with a clearly defined dependent and independent variable

Lessons & Assignments

Lessons

Lesson QMD Data Files
2.1: Intro to Visualizations Download sick_data.csv
2.2: More Visualizations Download sick_data.csv
2.3: Exploratory Data Analysis Download None
2.4: Intro to Statistical Testing Download fish_sick_data.csv
2.5: More Statistical Testing Download fish_sick_data.csv

Assignments

Assignment QMD Data Files Outputs
M2A1: Choosing a Research Question Download fish_sick_data.csv Download
M2A2: Analyzing Growth Rates Download tilapia_growth.csv Download
M2A3: Exploratory Data Analysis Download krill.csv, fur_seals.csv, gentoos_and_temps.csv, chinstraps_on_signy.csv None

GitHub

To clone the entire course, visit the course GitHub repository.