| 3 | <p>Students consider how to detect trends in large data sets against a background of variation. They use output from global climate models to examine projected climate change during the 21st century under a range of greenhouse gas emissions scenarios. Using Excel, they graph projected changes in temperature at particular locations over time and perform linear regressions. They compare projections of temperature change among emissions scenarios, across latitudinal gradients and between seasons. These exercises are adaptable to studying a wide range of climate parameters at any terrestrial location.</p> | 3 | <ul>
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| | | 4 | <li><strong>Course</strong>: BI 310 Statistical Data Analysis</li>
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| | | 5 | <li><strong>Course Level</strong>: Upper-level natural science majors</li>
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| | | 6 | <li><strong>Instructional Setting</strong>: Lecture/Lab (Students using computers in the classroom, collaborating synchronously)</li>
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| | | 7 | <li><strong>Implementation Timeframe</strong>: The course met for two two-hour-long blocks per week. The module occupied 3 class sessions in March and April, with a presentation on Monday May 1st (last week of classes). Some homework (i.e. outside of scheduled class time) was required to complete the data analyses.</li>
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| | | 8 | </ul> |
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