Unit 5: Data Analysis

After being in the field, listening to water, looking at trees and recording temperature, flow and culvert information your students are now looking at a lot of data. They are about to look at numbers that came from the samples they submitted to the lab and put those numbers together with data about the site. Moving students from that physical sample to a number in a table to a point on a graph to a statement linking the data to the hypothesis is an extraordinary journey. And, like any journey, should be taken with single steps.

Some of the best tools for understanding data are graphs. They are useful tools because they graphically represent those numbers, from those physical samples, in a common two-dimensional field… and this allows us to see the information all at once, and to make conclusions based on that “seeing”. Having your students use their graphs as a tool, not simply a product requires some work in understanding the making of meaningful graphs and the reading of graphs.

The creation of meaningful graphs involves a great deal of material that is normally covered in a Math class. Think about the possibility of team teaching this unit with a math teacher, possibly as a project that would receive both math and science credit.

By the end of this unit your students will have compiled and graphed their data, and interpreted their results.

Students need to be able to create graphs to help interpret their data and tell their research stories. More importantly, in school and in everyday life, students need to become conscious consumers, or interpreters, of information in a graphical form.

Guide students to:

• Organize their data
• Read graphs and understand what they show
• Create meaningful graphs
• Analyze graphical data to determine relationships or differences

Practice a Graph-a Day with your students

Display a graph at the beginning of each class (or put on your moodle or another intra-class site as homework) and ask:

• “What do you see?”
• “What does this graph say?”
• “What more can you ask?”

This exercise should take no more than 5 minutes. Start with fairly simple graphs and work to graphs with more variability.

Share the idea of variability

Ask your students to recall the sampling event. Discuss what might be different about their site now. Environmental data are inherently ‘messy’. There are many variables, or confounding factors, at play every second in every environment. The factors are often linked but will affect each sample a bit differently because never will all of those factors be exactly the same.

For example, if one variable is tree species and another is amount of litterfall, they might be linked—hardwood species will tend to have more leaves falling off than softwoods. Hopefully the study design in Unit 3 helped to record and therefore account for these confounding factors when feasible.

There will be many unforeseen confounding factors or variables you wish you had measured. Remind students that this information should be considered when trying to understand the data and may very well be useful when telling the research story at the end of the project.

Use the research question and hypothesis as guides to keep the data analysis on track

Although exploring the data can be a great learning experience, students might eventually lose focus and need redirection toward the hypothesis. Asking something like, “What is the question you’re asking of the data?” will help redirect.

Use the hypothetical graph created in Unit 2 as a template or cue to what a data product—like a graph or diagram - might look like

Although students may work on data analysis in separate groups, it is a good idea to compile all the data into one common spreadsheet or table so that each group has the same data to begin with.

• Activity 1: Data Warm-ups (essential)
• Activity 2: Data Organization (essential)
• Activity 3: Data Presentation (essential)
• Activity 4: Data Interpretation (essential)

See Lesson Resources

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