# Incorporating Open Data into Introductory Courses in Statistics

## TL;DR

This paper advocates integrating open data sources into introductory statistics courses to enhance engagement, relevance, and adherence to educational guidelines, supported by case studies and reproducible R code.

## Contribution

It introduces a practical approach for using open data in teaching, with detailed case studies and resources aligned with GAISE recommendations.

## Key findings

- Open data enhances student engagement and understanding.
- Case studies cover diverse topics like crime, housing, and rainfall.
- Reproducible R code supports implementation in classrooms.

## Abstract

The 2016 Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report emphasized six recommendations to teach introductory courses in statistics. Among them: use of real data with context and purpose. Many educators have created databases consisting of multiple data sets for use in class; sometimes making hundreds of data sets available. Yet `the context and purpose' component of the data may remain elusive if just a generic database is made available. We describe the use of open data in introductory courses. Countries and cities continue to share data through open data portals. Hence, educators can find regional data that engages their students more effectively. We present excerpts from case studies that show the application of statistical methods to data on: crime, housing, rainfall, tourist travel, and others. Data wrangling and discussion of results are recognized as important case study components. Thus the open data based case studies attend most GAISE College Report recommendations. Reproducible \textsf{R} code is made available for each case study. Example uses of open data in more advanced courses in statistics are also described.