Students will individually weigh a random sample of pennies. The data will be graphed to look for patterns, then explanations will be sought to explain these patterns. Some of the key ideas are using graphical representations of data to help identify patterns. This is a key concept in all sciences, including in the IceCube Neutrino Observatory - data
Even in Antarctica ice will melt. As the sun stays higher and higher in the sky as summer progresses, the warm sun causes the ice to melt. The questions that we are going to ask are: 1) Does clean ice (no sediment) or dirty ice (has sediment mixed in it) melt faster? and 2) Would the ice melt if
For this experiment, we are going to melt dirty ice (ice with lots of sediment/dirt in it) and clean ice (ice without sediment) from the Taylor Glacier. After we melt the ice, we are going to test the melt water for pH and conductivity, and then determine how much salt is actually in our ice samples. There are
This data plotting lesson compares different stratospheric ozone data collected at the South Pole in September 1969, September 1998, September 2008, January 1999, and January 2008. This ozone comparison activity allows students to make conclusions about the annual and seasonal ozone hole as well as overall ozone concentration changes over Antarctica. Students use authentic data collected at the
This data plotting lesson is about temperature changes throughout the atmosphere. The data was collected together with the ozone data in January 2008.
The temperature vs. altitude profile allows students to make conclusions about annual and seasonal temperature changes in the atmosphere up to about 35 kilometers in the stratosphere. The best part of this lesson is using