In this lesson, students begin working with the data that they have been collecting since the first lesson of the chapter in the class "data tracker." They are introduced to the first step in analyzing data: cleaning the data. Students will follow a guide in Code Studio, which demonstrates the common techniques of filtering and sorting data to familiarize themselves with its contents. Then they will correct errors they find in the data by either hand-correcting invalid values or deleting them. Finally they will categorize any free-text columns that were collected to prepare them for analysis. This lesson introduces many new skills with spreadsheets and reveals the sometimes subjective nature of data analysis.

In this lesson students learn how create their own summary tables from raw data. A summary table typically represents one or more aggregations (groupings of items) and computations that are performed on the raw dataset. In most spreadsheet programs, a summary table is called a pivot table. In the lesson, students learn how to make pivot tables in Google Sheets using a provided dataset. Then students turn to the data they’ve collected as a class and, with their partner, use pivot tables to investigate it further.

This article describes six collaborative and real data projects that engage elementary students in collecting and sharing local data and communicating with students across the country and world.

The students will gain an understanding of the sources of information used by geographers and apply what they have learned to analyzing primary sources and secondary sources and synthesizing what they have learned into a secondary source of information.