#### Data Analysis, As Real World as It Gets

Interactive Online Activities

Here are digital teaching resources that demonstrate how data and statistics are a vital part of learning mathematics in a meaningful context. The resource activities are often interdisciplinary, which makes them time-consuming to prepare, as additional expertise is often needed. But the payoffs can be huge: student engagement, in-depth learning, and a real-world context for learning mathematics.

The starting point for developing an interdisciplinary activity can be a teacher's personal interests or a student's passion. Are you a birder or pool player? Check out the ideas in Classroom FeederWatch, Backyard Birding--Research Project, or Analyzing Numeric and Geometric Patterns of Paper Pool below. Or if you want to begin with a simpler data collection lesson, take a look at Junk Mail below or Backpack Project.

Another approach is to look at situations in your community or larger world issues and have the students frame questions to investigate. Students may develop a passion for scientific inquiry when a topic can be analyzed with numbers. Requiring quality work and including a component about sharing results with the community will add value to an interdisciplinary contextual learning experience. Teachers may want to enlist a science teacher or community person to provide additional expertise. Whether thinking small activity or big project, be ready to be surprised at what the data analysis reveals!

#### Individual Lessons

Look out, pool sharks! Begin the study of data and statistics with this super student exploration where data are collected and analyzed while students apply mathematical topics studied in grades 6 and 7: factors, multiples, rectangles, and the meaning of being relatively prime. In the Paper Pool applet, a ball is hit from the lower left-hand corner of a grid-lined pool table at a 45-degree angle. Students modify the size of the rectangular pool table and observe how the ball always travels on diagonals of the grid squares. After gathering and organizing data, students look for patterns to predict the corner pocket into which a ball will fall and the number of side hits the ball makes as it moves on the table to a corner pocket. The goal is to determine how the number of hits, final pocket, and number of squares crossed depend upon the relative lengths of the sides of the pool table. Sounds like fun, doesn't it?

No one is immune from receiving junk mail, but just how much of it is really finding its way to your address? In this simple activity, data collection and analysis are a key part of a project to learn about the importance of recycling. For one week, students count and record the number of pieces of junk mail received in their homes. The display and organization of the data can be modified to address the data and statistics topics the class is working on.

Just how on-target are those weather forecasters we watch and listen to? In this webquest, students work in groups to track online weather reports for several locations over the course of three days and determine the accuracy of forecasts. Students develop an understanding of how weather can be described by measurable quantities, such as temperature, wind, and precipitation as they find and compare weather data found on the Internet, chart and graph data, and present their conclusions about forecasting. This straight-forward activity is suitable for students who are just beginning their work with data and statistics.

#### Projects

With this free online collaborative project, students measure the temperature and record the minutes of sunlight for one week. Data are collected on the web site, and average daily temperatures and amount of sunlight are compared. Students draw conclusions about how the distance from the equator influences temperature. If you like this collaborative project, be sure to check out Down the Drain: How Much Water Do You Use?, another collaborative data project from the Center for Innovation in Engineering and Science Education (CIESE).

If ocean travel is your passion, this site offers a way to spend time at sea without ever leaving your classroom. Here is a science project that uses actual data to help students investigate the science and history of the Gulf Stream. Math students can greatly benefit from the opportunity to collect data and draw conclusions based on the data. In the lesson called Current Now, students use real-time data and satellite images to determine how the Gulf Stream moves in the course of a year. In another activity, students use data about water temperature obtained from ships and buoys to determine the course of the Gulf Stream.

Be part of an annual event: Enroll your class in this free Internet-based collaborative project. Students discover which factors--room temperature, elevation, volume of water, or heating device--have the greatest influence on boiling point. Students boil water, record their data, and send it via email to be included in the site's database of results. Student activities focus on analyzing the compiled data to find answers to questions about how and why water boils.

Birds are everywhere, and here are ideas for creating a data collection project. Work with a science teacher and, possibly, an industrial tech teacher to expand this multiweek activity into a cross-curricular project to help students see how data analysis can support an understanding of nature.

These nine online lesson/activities investigate population growth and its impacts. Students use archived census and demographic data from the U.S. Census Bureau to model population growth and examine how population change affects the environment. Teachers will want to carefully review this resource to choose the activities most appropriate for their students' mathematics background. Linear, quadratic, and exponential functions are used in some lessons.

For this online data collection project, students monitor and report the number and type of animals killed by motor vehicles in their locale, along with information about the environmental conditions that may have contributed to an animal's death. The RoadKill Monitoring Project's goal is to make students aware of the environmental issues related to the death of wildlife on roads--the statistics are considered evidence of the conflict between humans and wildlife. Teachers can use the data to teach ecological principles, to portray information graphically, and to develop elementary concepts in statistical analysis.

#### Lesson and Project Collections

The Center for Innovation in Engineering and Science Education at the Stevens Institute of Technology develops free standards-based projects that offer real-time data found on the Internet and online collaborative projects linking classrooms from around the world. There are opportunities for cross-curricular activities and for rich experiences with data collection, data display, and for drawing conclusions or inferences based on the data. The Global Sun Temperature Project and the Gulf Stream Voyage highlighted above are two examples of this site's materials.

What better way to make data and statistics lessons real than to use the daily newspaper? Here are interdisciplinary lesson materials based on New York Times articles. The stories offer ways to draw on real-world issues and statistics to develop lessons in mathematics. For example, in one lesson, "students convert statistics about gun injuries into visual presentations, then use these as the basis for a poster campaign to teach children about the dangers of guns in home," while another lesson idea involves analyzing the job market for older workers.

This unit contains seven lessons with hands-on learning activities to help students explore statistics and probability. The lessons, designed for mentoring situations, may also be helpful to teachers new to teaching data and statistics. Each lesson features an overview of the mathematics, preparation guidelines, teaching tips, and suggestions for how to use each activity to develop specific mathematics concepts. Statistics activities focus on posing questions, gathering data and identifying bias, understanding measures of central tendency, representing data with graphs, and interpreting data.

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