Part 2 | Multivariate EDA
// examine relationships between variables //
Part 2 moves beyond individual variables to the heart of economic analysis: how variables relate to each other. We'll start with approaches for exploring the relationships between variables using python and spreadsheets. You'll learn the tools to spot patterns that reveal economic relationships. This is where data can start to tell stories.
Part 2.1 ~ Exploring Bivariate Relationships
Use scatter plots to visualize relationships between two numerical variables.
Concept 2.1 // Exploring Bivariate Relationships
Use a scatterplot in most cases
Exercise 2.1 // Coffee Production and GDP
Data on countries' coffee production and GDP
Homework 2.1
Due on Friday on Gradescope
Part 2.2 ~ Relationships Through Time
Use line plots to show changes over time.
Concept 2.2 // Relationships Through Time
Use boxplots, line plots, and scatterplots in most cases
Exercise 2.2 // Coffee & Economic Data
Data on the price of coffee, oil, and money
Homework 2.2
Due on Friday on Gradescope
Part 2.3 ~ Geographic Data
Use maps to show geographic differences.
Concept 2.3 // Geographic Data
Visualizing relationships between data in space
Exercise 2.3 // Restaurants and Zipcodes
Restaurants and the distance to downtown
MiniExams
MiniExam 2 covers everything in Part 2. Focus on interpreting relationships, working with time series data, and geographic analysis. You will begin to learn that if you understand the concepts and do the work in the examples and homework, you're going to be in good shape on the MiniExam.
MiniExams focuses on practical application of the concepts we've developed. Practice with Homework and Exercises to prepare effectively.
MiniExam 2 Demo
MiniExam 02 Demo covers all material from Parts 2.1 through 2.3 and tests your understanding of multivariate EDA concepts.